2026-04-04T02:55:53Z http://ijaim.net/journal/index.php/ijaim/oai

oai:ojs2.ijaim.net:article/1 2021-07-06T23:57:01Z ijaim:ART

oai:ojs3.ijaim.net:article/2 2025-12-30T17:01:52Z ijaim:ART

Application of Quality Function Development Method to Establish Application of New Product Development Information System Hung, Chien-Wen QFD New Product Development Fuzzy Method Decision Support System In the process of new product development, the customer's feeling is usually fuzzy phenomenon, how to evaluate various factors is to test the developer's intelligence, this study takes the new product development process as the research object, and applies the Quality Function expansion (QFD) method to establish a decision support system with fuzzy processing ability. In this study, the first development of quality function expansion (QFD) applied to Customer voice collection and analysis and conversion to product specifications. Then, the integration of fuzzy theory and the provision of different commodity development solutions as the best choice for products. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/2 10.47738/ijaim.v1i1.2 International Journal for Applied Information Management; Vol. 1 No. 1 (2021): Regular Issue: April 2021; 23-27 2776-8007 10.47738/ijaim.v1i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/2/3 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/3 2025-12-30T17:01:52Z ijaim:ART

Data Analytics Architectures for E-Commerce Platforms in Cloud Yeung, John Wong, Simon Tam, Alvin Cloud Computing Data Analytics Machine Learning E-Commerce Today, organizations not only need to manage larger volumes of data, but also generate insights from existing data. These insights help them understand better about their customers and predict market trends. With this initiative, they can take advantage of the cloud platform to achieve this goal because it manages higher data volume, speed and variation. This cloud platform enables them to provide elasticity and efficient computing and storage resources. They also provide many ready-to-use tools for building data analytics in various stages. Additionally, an on-demand pricing model allows organizations to pay for what they consume. It changes the organizational consumption model from capital expenditure to operational expenditure. It greatly minimizes initial capital investment to build data analytics solutions and implement other innovative ideas. This paper highlights the main reasons for encouraging organizations to build data analytics in the cloud. It also shows how to articulate data analytics frameworks for ecommerce platforms in the cloud and how to integrate machine learning models into data analytics processes, to create more sophisticated analyzes. AWS Amazon Web Services' premier public cloud platform is adopted to demonstrate these concepts and practices with real-life business cases. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/3 10.47738/ijaim.v1i1.3 International Journal for Applied Information Management; Vol. 1 No. 1 (2021): Regular Issue: April 2021; 1-5 2776-8007 10.47738/ijaim.v1i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/3/1 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/4 2025-12-30T17:01:52Z ijaim:ART

Understanding Users Attitude to Social Endorsement Advertising of Embarrassing Product Wang, Chih-Chien Yang, Yolande Chiang, Meng Social Media Advertising Privacy Concern Embarrassing Product Social Media Targeting Advertising Social Endorsement Advertising Advertising Knowledge Users on social media have increased rapidly in recent years, social media advertising has become a popular marketing tool for companies to promote their products. A feature of social media advertising is that marketers can use customers' online behavior to create customized advertisements, which are also known as targeting ads. In this study, we conducted experimental testing 2 (advertising type) X2 (product type) to see if increased knowledge of social advertising would influence users' attitudes towards ads. We separated two different types of advertising on Facebook, namely remarketing and social support, and two different types of products, which advertised general products and ads about embarrassing products. The results of this study are that the increase in advertising knowledge is able to (1) affect the perceived value of advertisements from different types of products and (2) different types of advertisements do not affect user attitudes towards advertisements. For future research, we recommend focusing primarily on the demographic and environmental variables of digital advertising users about embarrassing products. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/4 10.47738/ijaim.v1i1.4 International Journal for Applied Information Management; Vol. 1 No. 1 (2021): Regular Issue: April 2021; 6-22 2776-8007 10.47738/ijaim.v1i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/4/2 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/5 2025-12-30T17:01:52Z ijaim:ART

The Internet, The Cloud, and Information Technology Governance Asgarkhani, Mehdi Bartlett, Christopher Bracken, Dave IT Governance Cloud Computing Cloud Services IoT IT Governance Frameworks Information Technology Governance (ITG) has become a catalyst for strategic evaluation and deployment of IT solutions. Much of the concepts, the mechanisms, the processes, the frameworks, and the standards of ITG date back to the 1990s. A review of recent studies indicates an increased uptake of ITG practices within organizations – mostly via the adoption of ITG standards and frameworks. Within the last decade, we have witnessed rapid technological advancements which have in turn motivated radical changes in the management of IT infrastructure, deployment of IT applications, and delivery of IT services. For instance, Data Centers and Cloud Services have transformed the paradigm of infrastructure and application management in the IT sector. Moreover, sophisticated smart mobile solutions have made it possible to develop IoT solutions enabling smart cities and smart building initiatives. A review of timelines when ITG concepts and standards established suggest that they originated years before recent transformations in technology adoption took place. Some ITG standards show that the adoption of some cloud services motivated revision in some ITG frameworks. This study demonstrates that there is a possibility that some of the current ITG standards are not fine-tuned to reflect recent developments in the adoption of IT solutions and services. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/5 10.47738/ijaim.v1i1.5 International Journal for Applied Information Management; Vol. 1 No. 1 (2021): Regular Issue: April 2021; 28-35 2776-8007 10.47738/ijaim.v1i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/5/5 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/6 2025-12-30T17:01:52Z ijaim:ART

Location-Based Mobile Community Using Ants-Based Cluster Algorithm Srisa-an, Chetneti Mobile location based service WebMining Ant-based clustering A location based service (LBS) is widely used on modern smartphone around the world asits built-in features. Each smartphone can access a google API or map. People can therefore share their location (latitude and longitude) among friends. Many LBS spots can easily form “location based mobile community (LBMC).” Since the nodes are mobile, the community group changes dynamically and is unstructured. Ant-based clustering algorithm is a special kind of optimization technique which is highly suitable for finding the adaptive clustering for volatile networks. This Paper Aims To form a location based mobile community (LBMC) by using Ant-based clustering algorithm. Due to the mobile type community, a vanishing community problem is also stated in this paper. Instead of redo a whole algorithm again, we modify an original algorithm by applying a pheromone concept to handle a change. Our algorithm is named as ABCA & VP which stands for Ant-Based Clustering Algorithm with Vanishing problem. More than 5,000 samples from their latitude and longitude coordinates in Thailand. From an experiment, K-means clustering work well in small data size and low number of clusters. In Small size of data between 50 and 1000, our algorithm runs battery when a number of clusters reach 15 clusters. In a big data size (between 1,000 and 5,000 samples), our algorithm outperforms K-means clustering when a number of clusters reach 20 clusters. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/6 10.47738/ijaim.v1i1.6 International Journal for Applied Information Management; Vol. 1 No. 1 (2021): Regular Issue: April 2021; 36-41 2776-8007 10.47738/ijaim.v1i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/6/6 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/7 2025-12-30T17:02:24Z ijaim:ART

The Influence of Supply Chain Relationships on The Adoption of Open Standards Inter-Organizational Information Systems: A Conceptual Framework Pu, Xiaode Chan, Felix Chong, Alain Supply Chain Relationship Inter-Organizational Information System Open Standards Guanxi IOIS This study provides a conceptual framework to analyze where the formal and informal inter-organizational interactions influence the adoption decisions of open standards inter-organizational information systems (IOIS). Based on the Internet, open standards IOIS can help companies access to broader markets and make interfirm collaboration much easier and cheaper.In spite of these benefits, open standards IOIS have not been widely adopted by companies for external connection, which leads to questions about the importance of higher openness for inter-organizational systems. We argue that the characteristics of supply chain networks are fundamental for companies' choices of IOIS. The levels of linkages and interdependence between companies will affect how companies respond to external influences as well as heat demand for broader connection or tighter integration. Personal guanxi, the informal connections between individuals, also play an important part in companies' adoption decisions, especially in Asian countries where guanxi is prevalent business culture. Combining the different theoretical perspectives, we propose a conceptual framework and several integrative propositions for the analysis of the adoption decisions of open standards IOIS in the inter-organizational context. Bright Institute 2021-04-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/7 10.47738/ijaim.v1i3.7 International Journal for Applied Information Management; Vol. 1 No. 3 (2021): Regular Issue: September 2021; 91-98 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/7/7 Copyright (c) 2021 International Journal for Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/8 2025-12-30T17:02:10Z ijaim:ART

Making Sense of Wisdom Management Müürsepp, Peter knowledge-management leadership self-organization wisdom economy wisdom management An effective manager has to be wise. The paper analyzes different approaches to wisdom and makes proposals about how to apply them for making sense of wisdom management. The focus of the paper, however, is the relationship between wise management and wise leadership. At the basis of a definite understanding of knowledge management, we give the main reasons why wisdom is crucial for effective leadership, especially in self-organizing organizations. Practice is crucial but the basic human faculties of morality and creativity have to be accounted for as well. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/8 10.47738/ijaim.v1i2.8 International Journal for Applied Information Management; Vol. 1 No. 2 (2021): Regular Issue: July 2021; 63-69 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/8/10 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/9 2025-12-30T17:02:10Z ijaim:ART

Study of Career Education for Women: Development of Global Human Resources Hori, Mayumi Global Human Resources Career Education Working Women Globalization Empowerment Active Learning We are facing a rapid population decline caused by a declining birth rate. To keep our nation growing, we need to develop the capabilities of the next generation of diverse global human resources that provide us with a higher quality of life. To create innovation, it is necessary to develop global human resources who have advanced technical skills and combined capabilities such as thinking and management, as well as to create new added value. Unfortunately, women's working conditions are not the same as men's. Even though female labor force participation is increasing. the higher the level and level of education of women, there are still women who experience sex discrimination in the workplace where the traditional concept of gender roles still persists. The goal of Global Human Resource Development is to overcome the "inward tendencies" of students and to foster human resources who can positively respond to challenges and succeed in the global field, as a basis for increasing global competitiveness and strengthening brotherhood among nations. onment environment and maintain their career. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/9 10.47738/ijaim.v1i2.9 International Journal for Applied Information Management; Vol. 1 No. 2 (2021): Regular Issue: July 2021; 53-62 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/9/9 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/10 2025-12-30T17:02:10Z ijaim:ART

An Empirical Study to Understanding Students Continuance Intention Use of Multimedia Online Learning Hariguna, Taqwa TAM Multimedia online learning Continuance intention The purpose of this study was to assess students' ongoing intentions towards online multimedia learning such as perceived usefulness, ease of use, and flow experience. The sample of this study was 523 students who used off-campus/online learning resources and examined the content of online learning resources and their multimedia aspects. The Extended of Technology Acceptance Model (TAM) was used to predict students' continuing intentions. The results showed that students' intentions were positively influenced by their perceived usefulness, ease of use, and flow experience. It is suggested that the designer of multimedia online learning should be more specific in determining the target users to receive and cultivate a more positive sustainable intention. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/10 10.47738/ijaim.v1i2.10 International Journal for Applied Information Management; Vol. 1 No. 2 (2021): Regular Issue: July 2021; 42-52 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/10/8 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/11 2025-12-30T17:02:10Z ijaim:ART

The Effectiveness of The Body of Knowledge Process in The Startup Analysis of Efficiency by Applying Startup Management Body of Knowledge (SUBOK) Guide Hitoshi, Hirai Kamei, Shogo Ohashi, Masakazu Startups Entrepreneurs PMBOK SUBOK Guide CSV Entrepreneurs who create new businesses using innovative products and services that leverage the basic technologies of the 4th industrial revolution such as AI, IoT, Big Data and others technologies led by Germany and the United States have also emerged in Asia. Due to the diversification of consumer needs in recent years and the need for customer experience management to increase royalties, etc., the development cycle of new products and unique services tends to be shortened and how quickly they can be provided, which is a major problem. success factor. Meanwhile, in order to grow a business sustainably, it is also important to develop the right business strategy, build a governance structure, create value, and raise funds. In this thesis, we consider a startup as a project and describe the usefulness of implementing the Startup Body of Knowledge (SUBOK) Guide which systematizes the process to realize a startup quickly and reliably. In particular, we hypothesize that it is important to balance economic value and social value for startups, and consider the results of the implementation and analysis of the questionnaire. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/11 10.47738/ijaim.v1i2.11 International Journal for Applied Information Management; Vol. 1 No. 2 (2021): Regular Issue: July 2021; 70-80 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/11/11 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/12 2025-10-29T05:36:21Z ijaim:ART

oai:ojs3.ijaim.net:article/13 2025-12-30T17:02:24Z ijaim:ART

The Obsolescence of Man in The Digital Society Maillard, Dominique Promethean Pass Big data Digital society Cyber Security Commenting on the limitations of Man after the moral disasters of World War II and the logics of production inherent to the second industrial revolution, GuntherAnders had concluded to the “obsolescence of Man”. Anders pointed to the "Promethean gap" that exists between Man as an instrument among other instruments and his ability at encompassing the superior efficiency of the products he churned out. The new realities of production and trade, of human body engineering and power politics, as well as the shift from ownership to access, in the "digital society" hint that Gunther Anders's remark are still valid in the context of the third industrial revolution based on the Knowledge economy. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/13 10.47738/ijaim.v1i3.13 International Journal for Applied Information Management; Vol. 1 No. 3 (2021): Regular Issue: September 2021; 99-124 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/13/13 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/14 2025-12-30T17:02:24Z ijaim:ART

Leadership in a Global World Management Training Requirement Using The Example of The Asian Studies Program at University of Applied Sciences (HTWG) Konstanz Gertrud Thelen, Gabriele Value-based leadership training Global management and higher education Intercultural management This article demonstrates the need for higher education to systematically cultivate leadership competencies. Values-based leadership is emerging as an attractive international concept, and the related competencies that managers need stem from this. Approaches taken from intercultural communication theory and classical communication psychology show how effectively and clearly value-based actions (speech) can be taught as part of intercultural management training. Experience gained in the interdisciplinary study programs 'Asian Studies' and management (USA) and 'Business and Tourism Germany' (WDT) at HTWG Konstanzi is used as an example to demonstrate teaching formats that can be used to inculcate social competence, and in particular intercultural competence as a competence values-based leadership. This article describes how it is possible to incorporate appropriate teaching formats into management training curricula and also offers observations evaluating the effectiveness of such approaches, including using methods drawn from empirical social research. Bright Institute 2021-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/14 10.47738/ijaim.v1i3.14 International Journal for Applied Information Management; Vol. 1 No. 3 (2021): Regular Issue: September 2021; 125-135 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/14/14 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/15 2025-12-30T17:02:24Z ijaim:ART

A Study on Hospitality Education at University : Jal’s Philosophy Education as an Example Fujishima, Kiyohito Hospitality Hospitality Management JAL Philosophy Awareness reform Education From the viewpoint of hospitality management, which has received particular attention in recent years, this paper considers it at the point of employee education. In recent years in Japan's industrial world, almost all fields are concerned about the importance of hospitality. Indeed, holding the 2020 Tokyo Olympic Games is spurring the momentum. Against this background, in this paper the author studied what kinds of education can be assumed for fostering qualities that can demonstrate hospitality, and examined measures to train hospitality minds in education conducted in university. As a reference example, the author introduced JAL's "Philosophy Education". It is based on the author's 30-year employee experience in JAL. JAL's thorough awareness reform analyzed the success stories of employees' minds to rebuild their hospitality mindset and to protect corporate reconstruction from major blows. The center of awareness reform of JAL is implementation of "Philosophy Education". "JAL Philosophy" is the result of the goal of how to raise awareness of customer priority that was originally low, from reflection on bankruptcy. It is made of a basic attitude as a human being and a way of thinking that should always be conscious of. As a result of this, employees of JAL became able to act with consciousness of this philosophy as the origin of all ideas. As a result, the foundation for customer first was solidly completed. From this case study, the author can see that "Philosophy" is the origin of ideas and actions. This can be utilized in the field of university. Before going to society, consider philosophy as the source of their own actions and repeat consciousness in everyday life. When participating in seminars and outside-campus training, they put on the habit of acting based on their own philosophy. By doing this, their motto is reflected in how they contact people and when they act. Having one firm motto will allow them to become aware of themselves as a society and be able to move smoothly to society. Many young people like this can build society by performing their full hospitality and mind. Bright Institute 2021-07-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/15 10.47738/ijaim.v1i3.15 International Journal for Applied Information Management; Vol. 1 No. 3 (2021): Regular Issue: September 2021; 136-144 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/15/15 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/16 2025-12-30T17:02:24Z ijaim:ART

Construction of The E-Government Case Study of Japan and Estonia Tomura, Nozomi Uehara, Saki Kaneta, Konosuke Hara, Ryosuke Sasaki, Ryogo Tsuchida, Maho Shibuya, Ayu Yamashita, Maiko Internet Technology E-Commerce E-Government IT ICT The internet and PCs have been spreading in the world since the 1990s. The usage of these technologies not only in the business field but also in ordinary society. One of those business styles is Electronic Commerce. Most of the governments of countries and economists are taking these information technologies into their policies and developing them as their own IT policy. Above all, This paper summarized the history, structure, concrete outcomes and future plans for ICT, which is being advanced in Estonia, many of the ICT society including Japan is eager to realize, and introduces items that should be adopted to Japan. Bright Institute 2021-07-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/16 10.47738/ijaim.v1i3.16 International Journal for Applied Information Management; Vol. 1 No. 3 (2021): Regular Issue: September 2021; 145-151 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/16/16 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/17 2025-12-30T17:02:34Z ijaim:ART

Factors Affecting The Collaborative Relationships in Tourism Supply Chain Huyen Tran, Trang Thi Trust Commitment Personal Relationship Information Technology Tourism Supply Chain Structural Equation Modeling was employed to examine the influence of several factors: trust, commitment, personal relationship, application of information technology in the chain, customer orientation policy, asset specificity and behavioral uncertainty to the collaborative relationships between travel companies and their suppliers in the tourism supply chain. The results indicate that the first four factors have direct and positive impacts on this collaborative relationship. Furthermore, the study also confirmed the nexus between trust as well as customer orientation policy and the commitment among members in tourism supply chain. Bright Institute 2021-08-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/17 10.47738/ijaim.v1i4.17 International Journal for Applied Information Management; Vol. 1 No. 4 (2021): Regular Issue: December 2021; 152-164 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/17/17 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/18 2025-12-30T17:02:34Z ijaim:ART

Modelling The Relationship of Perceived Quality, Destination Image, and Tourist Satisfaction at The Destination Level Ky Vien, Nguyen Tourist Destination Perceived Quality Destination Image Tourist Satisfaction Today, the tourism sector in Vietnam has increasingly been a key element in job creation, economic development, and poverty alleviation. With its well-preserved cultural and natural diversity, Vietnam has been becoming a spotlight in the global tourism map. However, many tourist destinations in Vietnam are now struggling with ways to improve tourists’ satisfaction level and increase the return rate of tourists. Therefore, the tourism industry and government have to acknowledge how the tourists experienced and perceived the quality of a destination and the possibility of their return. The purpose of this study is twofold. Firstly, the study evaluates how tourists perceive the service quality of a tourist destination. Secondly, the study attempts to build a conceptual model linking tourists’ perceived quality, destination overall image and tourist satisfaction at the destination level. The study suggests more directions for future research: continuing to test the empirical validation and reliability of the conceptual model for a certain case study in Vietnam, and continuing to examine the moderating effects of the different demographic characteristics of the tourists (i.e. gender, age groups) on the relationships between tourists’ perceived quality, destination overall image and tourist satisfaction at the destination level. Bright Institute 2021-08-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/18 10.47738/ijaim.v1i4.18 International Journal for Applied Information Management; Vol. 1 No. 4 (2021): Regular Issue: December 2021; 165-172 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/18/18 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/19 2025-12-30T17:02:34Z ijaim:ART

Difficulties of Integrating Human Resources Management Globally by Japanese Corporations Takakuwa, Kentaro J-system H-system Labor Market Individual Human Asset Context-Oriented Human Asset Incentive System International enterprises should integrate human resource management globally under a multi-dimensional global market. But the globalized level of Japanese companies’ human resource management has been low for decades. This might have structural causes, then they couldn't execute necessary policy change. I found this structural problem which prevents Japanese companies from offering attractive job opportunities to foreign workers through international comparison of the relation between labor market and incentive system to attitudes of work. The experienced labor market is imperfect only in Japan. This situation enhances the accumulation of “context-oriented human assets”. Seniority based rewards systems promote them to co-operate then increase the performance of this kind of human asset. In contrast, “independent human asset” would be accumulated in other countries, such as South Korea, China, Indonesia, United States and Brazil, except Germany. The experienced labor market is relatively perfect in these countries, and those who put priority on both good rewards and clear career path when seeking job opportunities get good rewards. Because this kind of incentive system seen in the countries except Japan and Germany have inconsistency with that is seen in Japanese homeland office, Japanese companies couldn’t integrate human resource management globally. Japanese companies need a fundamental change of organizational architecture to regain the international competitiveness and utilize the new market opportunity overseas. Bright Institute 2021-08-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/19 10.47738/ijaim.v1i4.19 International Journal for Applied Information Management; Vol. 1 No. 4 (2021): Regular Issue: December 2021; 173-186 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/19/19 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/20 2025-12-30T17:02:34Z ijaim:ART

The Effects of Safety Management Systems, Attitude and Commitment on Safety Behaviors and Performance Su, Wen-Jywan Safety Culture Safety Performance Safety Management System Structural Equation Model Safety culture is part of organizational culture, and assessing corporate safety culture as a means of increasing safety performance is gaining acceptance. Based on Cooper’s reciprocal model, this paper studied the effects of managerial safety commitment and workers’ personal safety attitude as well as the organization safety management system (SMS) towards individual safety compliance and participation, and their relationship with safety performance. Questionnaires were obtained from employees and contractors of a large steel company in 14 functional departments. Modified reciprocal safety models were verified by structural equation model (SEM). The SMS and personal attitude have effects on compliance behavior. Participation behavior was influenced by the SMS and management commitment. Perceived performance was affected by compliance and participation behavior and management commitment as well. Successful implementation of a SMS will strongly motivate the workers’ participation in safety activities and compliance with safety regulation. Managers’ strong commitment toward safety is essential to foster safety performance. A Good safety attitude will motivate the worker to follow safety regulations for self-protection but does not encourage him to participate in safety activities. Increasing managerial safety commitment such as concerns about workers’ safety participation activities and participation safety activities will directly motivate the worker’s safety participation. Bright Institute 2021-08-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/20 10.47738/ijaim.v1i4.20 International Journal for Applied Information Management; Vol. 1 No. 4 (2021): Regular Issue: December 2021; 187-200 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/20/20 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/21 2025-12-30T17:02:34Z ijaim:ART

Proposing a Theoretical Model to Determine Factors Affecting on Job Satisfaction, Job Performance and Employees Loyalty For Technology Information (IT) Workers Kim Phuong, Tran Thi Trung Vinh, Tran Workplace environment Pay and Promotion potential Fairness Workplace relationship Job satisfaction Job performance Employee loyalty Information technology (IT) industry in Vietnam has had steady development steps to continuously strengthen its position and role in the sectors such as politics, social - economics, security - defense for further integration into the world. There are many companies now competing in this area. In the unpredictable and competitive business environment, employee plays a vital role for nearly all organizations, thus the important issue is to try to deeply understand work related attitudes and behaviors that affect the well- being of an employee as well as the effective function of an organization. Hence, this paper adapted several previous models in order to find out the influence of workplace environment, pay and promotion potential, fairness and workplace relationship on the level of job satisfaction and examine the relationships among job satisfaction, job performance and employee loyalty for IT workers in Vietnam. Bright Institute 2021-08-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/21 10.47738/ijaim.v1i4.21 International Journal for Applied Information Management; Vol. 1 No. 4 (2021): Regular Issue: December 2021; 201-209 2776-8007 eng http://ijaim.net/journal/index.php/ijaim/article/view/21/21 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/22 2025-12-30T17:02:46Z ijaim:ART

Research on New Regional Creation Business Model Utilizing Social Network and Crowdfunding Matsuda, Takefumi Social Networks Social Capital Regional Vitalization Crowdfunding Bridging SNS The development of IT has made it possible to create a bridge between regional and urban residents using things like SNS and crowd funding. The decline of local communities due to a reduced population is an important factor that has an impact on the future of the entirety of Japan. In response to this problem, the young generation is making attempts to vitalize regions based on a relationship of sharing, co-creation, and sympathy that come from sharing the same space by using IT. The general idea of a share village is that old Japanese-style homes in regions are regarded as villages and multiple hometown areas can be chosen for SATOGAERI (Country life experience). This project is an initiative with the objective of preserving old Japanese-style homes that are pieces of history and saving Japan's original landscape for the next 100 years. Thus, bridges are built between regional residents and the resources of urban residents based on a perspective of generating social capital and focusing on structures that are maintained by many people. This paper examines the possibility of generating new social capital through regional vitalization and reviving local communities by creating such bridges, and it presents a new design for local communities. Bright Institute 2021-10-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/22 10.47738/ijaim.v2i1.22 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 1-12 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/22/28 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/23 2025-12-30T17:02:46Z ijaim:ART

Determinants of Trade Balance in Vietnam During 1997-2015 To, Trung-Thanh Trade balance VECM REER FDI NFA This paper investigates the determinants of trade balance in Vietnam during 1997-2015, based on the restricted VECM model. The result suggests that in the long run, the openness has negative impact on trade balance. The initial level of NFA is negatively associated with trade balance. The more developed financial system can improve trade balance meanwhile higher income can worsen it. REER could have no close relationship with trade balance. Increasing FDI can contribute to trade deficit meanwhile capital mobility could improve trade balance. The trade balance also has a self-adjusting mechanism towards long-run equilibrium after the shocks to explanatory variables. Bright Institute 2021-10-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/23 10.47738/ijaim.v2i1.23 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 13-25 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/23/29 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/24 2025-12-30T17:02:46Z ijaim:ART

Purchasing Power Parity Between Vietnam and United States Thi Du, Hoang Xuan Tho, Nguyen Purchasing Power Parity Exchange Rate Relative Price This study uses the annual data of consumer price index, exchange rate and inflation rates spanned from 1986 to 2014 in order to observe whether the PPP hypothesis holds between Vietnam and United States. First, the findings come out based on the graph aproach which is used in order to examine both short-run and long-run PPP. Second, the Engle-Granger approach is applied in order to test for the long – run PPP again. In the short-run, the result from the graph approach indicates that PPP holds during hyperinflation years. After hyperinflation period, the exchange rate and relative price tend to be close together in several years. This finding in the short-run seems to reveal a good guide in the long-run PPP. Both graph and the Engle-Granger approach show the same result in the long –run. Upon the stationary testing, the finding of the Engle-Granger approach demonstrates that residuals from the estimation are stationary, therefore, there is an existence of a long-run relationship between nominal and real exchange rate. In other way, PPP seems to hold between Vietnam and United States. The result leads to the implication that multinational companies should set the same prices for products in Vietnam and United States market based on PPP. Otherwise, investors can gain profit through arbitrage strategies. Bright Institute 2021-10-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/24 10.47738/ijaim.v2i1.24 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 26-33 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/24/30 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/25 2025-12-30T17:02:46Z ijaim:ART

An Exploration Into Trust and Privacy Management in a Digital Age Lin, Yue Jer Digital Age Fair Information Practices Privacy Management This study aims to inspect the effects of the privacy management and realize the relationship between use of trust and the quality of the privacy policy for the sites. This research applied four criteria of notice, access, choice and security that were identified by the FTC as Fair Information Practice to assess 476 websites for the trust and privacy management. Results indicated that approximately 36% of the websites used a trustmark, and that HiTrust/VeriSign was the most commonly used by businesses. The preferred trustmark varied by industry, such as sports sites preferring Verified by VISA, real estate sites preferring SOSA, telecommunication sites preferring HiTrust/VeriSign, and travel sites preferring TWCA. However, BBB Online and TRUSTe were displayed very hardly. The main findings showed that there were no obvious relationships between the use of trust marks and the notice criterion. On the contrary, there were very strong relationships between the use of trust marks and the access and choice criteria for all industries and overall. Bright Institute 2021-09-13 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/25 10.47738/ijaim.v2i1.25 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 34-43 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/25/23 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/26 2025-12-30T17:02:46Z ijaim:ART

Knowledge-Driven Automated Service Composition as a Method for Developing Decision Support Systems Fujishima, Kiyohito DSS Knowledge Decision Support A decision support system often necessitates a large amount of effort from both a domain modeling and technological standpoint. Using automated service composition, the study provides a method for minimizing the complexity of decision support system development. The justification for the approach is that many software systems (including decision support systems) today are based on service-oriented architecture, and the development of such systems may be described to some extent as a building composition of services that meet the required requirements. Automated planning algorithms can successfully address the difficulty of creating such compositions. The functional framework of decision support systems, requirements analysis for configurable service-oriented decision support systems and its primary components, and a conceptual model of a configurable service-oriented decision support system are all presented in the article. Bright Institute 2021-09-13 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/26 10.47738/ijaim.v2i1.26 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 44-49 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/26/22 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/27 2025-12-30T17:03:01Z ijaim:ART

EOQ Development Model in Optimize Raw Material Inventory Kartika, I Made Adi Suwandana, I Made Bagus Wirya Gupta, I Gusti Denny Herlambang, Putu Gede Raw material inventory Distribution EOQ The purpose of this study was to determine the amount of safety inventory, order frequency, minimum inventory, maximum inventory limit, total Melon product inventory costs needed by PT. Rajawali Asia Bali uses the EOQ method. Data analyzed using the EOQ method shows that PT. Rajawali Asia Bali safety stock, it is very necessary to support the smooth distribution process that takes place. In accordance with the calculations with the formula, there is a safety stock that must be provided by PT. Rajawali Asia Bali is equal to 7,201 boxes. Planning for Sweet Corn products at PT. Rajawali Asia Bali using the EOQ method has 48.069 boxes. Bright Institute 2021-12-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/27 10.47738/ijaim.v2i2.27 International Journal for Applied Information Management; Vol. 2 No. 2 (2022): Regular Issue: July 2022; 59-65 2776-8007 10.47738/ijaim.v2i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/27/32 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/28 2025-12-30T17:03:01Z ijaim:ART

Intelligent POIs Recommender System Based on Time Series Analysis with Seasonal Adjustment Chen, Meng-Kuan Wei, Hsin-Wen Lee, Wei-Tsong Recommender System Time Series Analysis Long-term Trend Analysis Seasonal Adjustment Recommender systems have been applied on a variety of applications including movies, music, news, books, research articles, search queries, and travel information. Instead of searching travel information from the extremely huge amount of travel data, a personalized travel recommender system is desired. However, an inappropriate travel recommendation may result from a wrong season, even if it is already a correct location. The current recommender systems from time to time make an inappropriate commendation without considering the seasonal factor. In order to resolve the discrepancy, the seasonal factor should have been taken into consideration when making a good travel recommender system. Therefore, this study has taken the trend analysis, time series, and seasonal factor into considerations to cope with the above mentioned discrepancy and to make the travel recommender system renders a better fit. Bright Institute 2021-12-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/28 10.47738/ijaim.v2i2.28 International Journal for Applied Information Management; Vol. 2 No. 2 (2022): Regular Issue: July 2022; 66-80 2776-8007 10.47738/ijaim.v2i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/28/33 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/29 2025-12-30T17:02:46Z ijaim:ART

Financial Performance Innovation Since Digital Technology Entered Indonesian MSMEs Maharini Adiandari, Ade Commercial Innovation Digital Technology Small Business MSME This study aimed to understand the accounting performance innovation of MSME business people since digital technology has become a business supporter. Before searching the data, we tried to understand the core of the problem, and then we searched the data with the help of electronically using keyword searches. Next, we will continue with the data studied by involving the data coding system to critically evaluate the interpretation of the data in-depth so that we conclude from the data that we harmonize with the meaning and intent of this research question. The data sources that we look at are some international journal publications that actively discuss financial and digital issues for Indonesian small businesses. The applications we mean are ah and France, Sage publications, Google books, emerald publications, and some websites that we visited to get data that could fill the discussion of this study. This study fully uses secondary data, namely data published by previous studies, and we report in a descriptive qualitative article under a phenomenological approach. This study system explores the data as comprehensively to understand a field of study, becoming valid and convincing data in answering and filling out the discussion. Based on the study data and discussion, we can summarize that many MSME drivers can still not apply digital technology in their financial system, which makes innovation in business implementation, especially financial reporting. Thus, this finding becomes a meaningful input in studying relevant themes in the future. Bright Institute 2021-12-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/29 10.47738/ijaim.v2i1.29 International Journal for Applied Information Management; Vol. 2 No. 1 (2022): Regular Issue: April 2022; 50-58 2776-8007 10.47738/ijaim.v2i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/29/31 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/30 2025-12-30T17:03:01Z ijaim:ART

Human Capital Management of Government Internal Supervisory at the Ministry of Defense of the Republic Indonesia Efendi, Afwan Purwana, Dedi Buchdadi, Agung Dharmawan Human Capital Management Supervisory Apparatus Internal Oversight Balanced Scorecard Ministry of Defense Organizational Goals The results of the study found that the government internal supervisory performance was not yet optimal in supporting the achievement of the vision and mission as well as organizational goals. This study aims to provide an overview of human capital management practices of government internal supervisory at the Ministry of Defense by using a balanced scorecard perspective approach from a stakeholder perspective, a business internal process perspective, a learning and growth perspective and a financial perspective. This study used a qualitative method with a case study approach and used purposive and snowball sampling. There are 19 informants including a structural officer, the auditor, and personnel from the National Financial and Development Supervisory Board. It is noted that the quality of the auditors does not fulfill the required quality. The recommendations include the importance of improving aspects of human resource competence through education and training for certification of the Functional Auditor (JFA) according to the level of the position, improving the quality of the code of ethics, improving the recruitment system, and increasing the budget for providing the operational budget and enhancing the quality of the government internal supervisory. Bright Institute 2021-12-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/30 10.47738/ijaim.v2i2.30 International Journal for Applied Information Management; Vol. 2 No. 2 (2022): Regular Issue: July 2022; 81-89 2776-8007 10.47738/ijaim.v2i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/30/34 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/31 2025-12-30T17:03:01Z ijaim:ART

Exploring Social Media Use and Civic Engagement on the Discussion of Antinuclear Issue Lin, Cathy S. Kuo, Feng Yang Hung, Ching Ya Social Media Anti-Nuclear Energy Self-Presentation Efficacy Civic Engagement Social media has brought a new communication revolution allowing users to connect, share, and discuss public & social opinions with others. The new look at social media has shaped social movements, and provides a fair voice to anyone who can be heard online. This research explores individuals’ civic engagement concerning the environmental issue of nuclear energy on social media. Nuclear energy is a global, social, and environmental issue, the research variables included in this study are self-presentation efficacy, fear of social isolation and stigma consciousness. The findings from this study will have implications for both research and practices, especially help understanding the civic engagement of social movement on social media. Bright Institute 2021-12-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/31 10.47738/ijaim.v2i2.31 International Journal for Applied Information Management; Vol. 2 No. 2 (2022): Regular Issue: July 2022; 90-96 2776-8007 10.47738/ijaim.v2i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/31/35 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/32 2025-12-30T17:03:01Z ijaim:ART

The Influence of Interpersonal Communication, Universal-Diverse Orientation (UDO), and Self-Efficacy on the Quality of Administrative Services at State University of Jakarta Yusuf, Ifatuhoriah Purwana, Dedi Buchdadi , Agung Dharmawan Interpersonal Communication Universal-Diverse Orientation (UDO) Self Efficacy Administrative Service Quality This study aims to determine the direct effect of interpersonal communication, universal-diverse orientation (UDO), and self-efficacy on the quality of administrative services, as well as to determine the indirect effect of interpersonal communication and universal-diverse orientation (UDO) through self-efficacy on the quality of administrative services at State University of Jakarta. The research used was a survey with a causal design. The number of sample respondents was determined as 178 employees, the sampling technique was carried out by simple random (sample random sampling) from 230 employees of the State University of Jakarta.  The results of this study indicate that; (1). There is a positive direct effect of Interpersonal Communication on the Quality of Academic Services, (2). There is a positive direct influence Universal-Diverse Orientation (UDO) on the Quality of Academic Services, (3). There is a positive direct effect of Self Efficacy on Academic Service Quality., (4) There is a positive direct influence of Interpersonal Communication on Self Efficacy, (5) There is a positive direct influence of Universal-Diverse Orientation (UDO) on Self Efficacy. The novelty in this research is that research conducted at this time is research looking at several variations of variables such as the influence of interpersonal communication, universal-diverse orientation (UDO), and self-efficacy on the quality of administrative services and quality variables as independent variables. Bright Institute 2021-12-17 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/32 10.47738/ijaim.v2i2.32 International Journal for Applied Information Management; Vol. 2 No. 2 (2022): Regular Issue: July 2022; 97-105 2776-8007 10.47738/ijaim.v2i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/32/36 Copyright (c) 2021 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/33 2025-12-30T17:03:13Z ijaim:ART

A Study on the Relationships Among Personality Traits, Gender and Customer Knowledge Preferences Tseng, Shu-Mei Liang, Chau-Wei Tsai, Hsien-Lein Customer Knowledge Preference Gender Personality Traits Empirical evidence suggests that an enterprise can obtain knowledge related to new demands about products or services through interactions with customers, which can be helpful references leading to the enhancement of customer satisfaction and loyalty. However, little is known about the antecedents of customer knowledge preferences. Therefore, this study begins with a literature review followed by the use of a questionnaire method to investigate the relationships among personality traits, gender and customer knowledge preferences. Results indicate that three of the five personality traits, as measured by the Big-5 factors of personality, contribute to explain customer knowledge preferences. Gender has a moderating effect on the traits of emotional stability and customer knowledge preferences. Bright Institute 2022-02-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/33 10.47738/ijaim.v2i3.33 International Journal for Applied Information Management; Vol. 2 No. 3 (2022): Regular Issue: September 2022; 01-17 2776-8007 10.47738/ijaim.v2i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/33/41 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/34 2025-02-05T21:54:25Z ijaim:ART

oai:ojs3.ijaim.net:article/35 2025-12-30T17:03:13Z ijaim:ART

The Influence of Transformational Leadership, Emotional Intelligence, Organizational Climate, and Teamwork, Towards Organizational Citizenship Behavior of Civil Servants Hamid, Fadlun A Widodo, Suparno Eko Buchdadi, Agung Dharmawan Transformational Leadership Emotional Intelligence Organizational Climate Citizen Behavior The purpose of this study was to ascertain the direct positive effect of transformational leadership, emotional intelligence, organizational climate, and teamwork on the organizational citizenship behavior of civil servants at the Central Sulawesi Province Education and Culture Office. The novelty of this research is that no prior study has examined the effect of transformational leadership, emotional intelligence, organizational climate, and teamwork on the organizational citizenship behavior of Civil Servants at the Education and Culture Office of Central Sulawesi Province, both methodologically and practically. This research employs a survey method and falls under the category of quantitative research. The population of this study was 433 individuals, and the sample size was 100 individuals drawn using a random sampling technique. Interviews, questionnaires, and documentation studies were used to collect data. The findings of this study are as follows: (1) transformational leadership (X1) and organizational climate (X3) have a direct positive effect on organizational citizenship behavior (Y); (2) emotional intelligence (X2) and organizational climate (X3) have a direct positive effect on teamwork (X4); (3) emotional intelligence and teamwork have no direct positive effect on organizational citizenship behavior; and (2) transformational leadership does not have a direct positive effect on organizational citizenship behavior. Bright Institute 2022-02-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/35 10.47738/ijaim.v2i3.35 International Journal for Applied Information Management; Vol. 2 No. 3 (2022): Regular Issue: September 2022; 26-39 2776-8007 10.47738/ijaim.v2i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/35/39 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/36 2025-12-30T17:03:13Z ijaim:ART

The Effect of Work Motivation and Perception of College Support on Organizational Commitment and Organizational Citizenship Behavior in BKPSDM, Tangerang District Nordat, Iskandar Tola, Burhanudin Yasin, Mahmudin Work Motivation Perception of College Support Organizational Commitment Organizational Citizenship Behavior This study aims to analyze the effect of employee motivation, perceptions of colleague support, and organizational commitment to organizational citizenship behavior in BKPSDM, Tangerang District. This study uses an Associative Quantitative approach, namely by studying the causal relationship between independent variables and dependent variables. The data collection methods used were survey methods and structural equation modeling (SEM) analysis techniques with SMART PLS 3 software. The population in this study were all employees in the BKPSDM environment and civil servants managing personnel within the OPD area of Tangerang Regency, as many as 140 people. While the sample used in this study were 100 people. The result showed that Organizational Commitment has significant direct effect on Organizational Citizenship Behavior, Perceived Coworker Support has significant direct effect on Organizational Commitment, Work Motivation has significant direct effect on Organizational Commitment, Work Motivation has significant indirect effect on Organizational Citizenship Behavior through Organizational Commitment. Meanwhile, Perceived Coworker Support has not significant direct effect on Organizational Citizenship Behavior, Work Motivation has not significant direct effect on Organizational Citizenship Behavior, and also Work Motivation has not significant indirect effect on Organizational Commitment through Organizational Citizenship Behavior. Bright Institute 2022-02-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/36 10.47738/ijaim.v2i3.36 International Journal for Applied Information Management; Vol. 2 No. 3 (2022): Regular Issue: September 2022; 40-49 2776-8007 10.47738/ijaim.v2i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/36/38 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/37 2025-12-30T17:03:13Z ijaim:ART

Small and Medium Enterprises (SMEs) with SWOT Analysis Method Rakhmansyah, Mohamad Wahyuningsih, Tri Srenggini, Abdullah Dwi Gunawan, I Ketut SWOT Analysis Social Media Marketing Strategy This study aims to determine the strengths, weaknesses, opportunities and threats to SMEs in utilizing social media as a marketing tool and to find out the most effective marketing strategies to run in order to increase sales. The method used is SWOT analysis, and in data processing using excel. In collecting data using a questionnaire method distributed in the January 2021 period with a total of 226 respondents. The results obtained by SMEs in utilizing social media as marketing are in quadrant I, which means that the strategy used is a growth strategy, namely the SO strategy which is a strategy that uses strengths to take advantage of opportunities that exist in SMEs. Its implementation is to increase the intensity of promotions, maintain product and service quality, maintain and increase customer trust, be communicative to customers. Bright Institute 2022-02-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/37 10.47738/ijaim.v2i3.37 International Journal for Applied Information Management; Vol. 2 No. 3 (2022): Regular Issue: September 2022; 50-57 2776-8007 10.47738/ijaim.v2i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/37/37 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/38 2025-12-30T17:03:25Z ijaim:ART

Evaluation of the National Values Construction Program for National Resilience Institute Republic of Indonesia (LEMHANNAS RI) Yuhastihar Hamidah Madhakomala Human Resource National Values Lemhannas RI CIPP The Program for Strengthening National Values was established by Presidential Regulation Number 67 of 2007 addressing Lemhannas RI. This study's goal is to assess Lemhannas RI's national values building initiative from 2007. This research used the CIPP program assessment paradigm and included observation, interviews, questionnaires, Focus Group Discussions, and document examination. The research included 220 national values strengthening graduates, 4 (four) RI Lemhannas officials who implemented the stabilization program, 3 (three) Lemhannas RI Professional Staff who became resource people for the stabilization program, and 10 (ten) alumni. The findings of the context assessment indicated that Lemhannas RI's implementation of the Program for the Consolidation of National Values had a strong legal foundation, clear and realistic aims and objectives, and significant community needs. For example, inadequate cost support, inadequate curriculum support, inadequate human resource (HR) support, inadequate infrastructure support, and inadequate recruitment participants were found in the Input evaluation. The program may be carried out as intended, and the process monitoring and assessment can offer an overview of quantifiable outcomes. The effect of the strengthening program on alumni is excellent, as shown by changes in attitudes, motives, and actions. Bright Institute 2022-05-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/38 10.47738/ijaim.v2i4.38 International Journal for Applied Information Management; Vol. 2 No. 4 (2022): Regular Issue: December 2022; 58-72 2776-8007 10.47738/ijaim.v2i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/38/42 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/39 2025-12-30T17:03:25Z ijaim:ART

Information and Communication Technology and Knowledge Sharing: a Literary Referential Study Bin Maalawi, Turki Rahman Obaid, Abdul Communication Technology Knowledge Sharing ICT This study examines "information and communication technology and knowledge sharing" articles. It discusses the topic's literary relevance. Researchers examined research, studies, and Arab and global trends. The study read books. Originally, scientific databases tracked the expansion of ICT in Arab and foreign intellectual output. The first computer, the IBM 7001, was released in the mid-1970s, igniting the expansion of information and communication technology (ALTAIR). Then followed a study on ICT's impact on businesses. It was detected 7.5 million times between 1999 and 2020. 21 studies centered on the Arab world. Information sharing via research and monitoring was also explored in the study. Wilson investigated knowledge sharing to improve organizational performance in 1983. From 1980 to 2020, the number of citations for knowledge sharing in research titles in scientific articles continuously increased, reaching over a thousand. The notion of information technology and knowledge sharing developed in 1990, when Hendersk said that knowledge sharing needed information and communication technology. Robert Yinks et al. examined IT & K in 1991 AD. This study addresses ICT and knowledge sharing. From 1991 to 2020, the digital index of "information and communication technology and knowledge sharing" reveals a lot of international research on the issue. From 2005 to 2017, several studies on the same topic were presented at conferences, workshops, and scholarly forums. These studies emphasized IT and knowledge transfer. An international study on public organizations exists. The Internet, intranet, extranet, and other ICT have been studied for their influence on knowledge exchange. Other studies linked ICT to corporate culture, performance, job happiness, organizational justice, communication, and other management necessities. Another study examined how ICT may promote knowledge sharing. Some studies looked at social media's impact on knowledge sharing. Bright Institute 2022-05-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/39 10.47738/ijaim.v2i4.39 International Journal for Applied Information Management; Vol. 2 No. 4 (2022): Regular Issue: December 2022; 73-83 2776-8007 10.47738/ijaim.v2i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/39/43 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/40 2025-12-30T17:03:25Z ijaim:ART

The Strategic Plan of the Information Technology Deanship - King Abdulaziz University- Saudi Arabia Al-Jedibi, Wagdy Personality Traits Gender Customer Knowledge Preference IT has now become an integral part of modern university life to the extent that various IT institutions are required to act as partners within the academic institutions rather than just providing them with secure and reliable IT infrastructure and services. Thus, in light of these successive accelerating developments, and keeping pace with the vision of the Kingdom of Saudi Arabia 2030 in relation to developing the higher education system that focuses on granting Saudi universities a great deal of administrative and financial independence, the Deanship of Information Technology at King Abdulaziz University works hard to activate its leading role in providing modern technical services for various sectors inside and outside the university through framing and preparing a new strategic vision in line with the changes taking place in the work environment at the university. Essentially, this new vision takes into account the fact that King Abdulaziz University is a research and educational institution at a global level with global interests and with constantly increasing technological environment demands that are vital to support its overall competitiveness and success. By the end of this article, the willingness of our community members to meet and engage in a deep and comprehensive discussion of the strategic strengths, weaknesses, opportunities and threats of the IT environment “based on the use of the SWOT approach” is in itself a solid evidence of our community’s excellent ability to work together towards achieving a set of common ambitious goals. Ultimately, the process of planning and designing the strategic plan allowed participants from all over the campus to interact with each other and reach a common understanding of the university’s technological goals and the strategic actions required to achieve those goals namely in relation to supporting innovation in research and education, helping people use technology more effectively, and providing secure services and systems for all the university environment components. Bright Institute 2022-05-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/40 10.47738/ijaim.v2i4.40 International Journal for Applied Information Management; Vol. 2 No. 4 (2022): Regular Issue: December 2022; 84-94 2776-8007 10.47738/ijaim.v2i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/40/44 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/41 2025-11-21T05:13:05Z ijaim:ART

A Decision Support System for Priority Calculation of Travel Routes using Analytical Hierarchy Process Izha, Rahadian M Ramadhani, Yogi DSS MCDM AHP Currently, selecting a route to reach a specific destination has become more convenient due to map and navigation services such as Google Maps, Apple Maps, Bing Maps, OpenStreetMap, and many more. These services provide users with the most efficient routes using their own algorithms. However, we believe that users would obtain more convincing results if they could choose a route based on their own criteria. This paper proposes a method for selecting a route using the Analytical Hierarchy Process (AHP). AHP allows users to choose criteria, whether subjective or objective, to compare values and calculate priorities, resulting in more convincing results for users. By using AHP, users can determine the most suitable route according to their preferences and needs, providing a more personalized and satisfactory experience. This method could be expanded in the future by integrating machine learning algorithms and real-time traffic data to further improve the accuracy of the selected route. Bright Institute 2023-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/41 10.47738/ijaim.v3i1.41 International Journal for Applied Information Management; Vol. 3 No. 1 (2023): Regular Issue: April 2023; 33-45 2776-8007 10.47738/ijaim.v3i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/41/50 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/42 2025-12-30T17:03:25Z ijaim:ART

A Knowledge Behavioral and Intelligence Management in Fostering Entrepreneurship for Modern Industries Alfazzi, Faiz Intelligence Strategic Intelligence Organization Development Entrepreneurial Behavior The major goal of this work is to investigate the relation between management strategic intelligence (SI), organizational Development (OD), and Entrepreneurial Behavior (EB) in government agencies in developing nations. In a larger sense, while knowledge and experience have separate effects on an entrepreneur's decision-making process and behavior, there have been no proven research on how similar characteristics affected decisions and behaviors during the entrepreneurial transition. The influence of knowledge and experience was investigated in this study. The C-square test indicated that knowledge and experience are statistically relevant for entrepreneurs, demonstrating vision, independence, achievement, and responsiveness, using the smart approach for data collecting and analysis. This research focused on business decisions have been made.  The indirect impact demonstrates that supervisors combination of knowledge management, emotional intelligence, and entrepreneurial abilities has a statistically favorable influence on organizational innovation. This technique contributes to the scientific as well as economic consequences. Scientific impact, in the form of new knowledge that reinforces the value of executives as innovation catalysts; and a new socio-economic management tool to improve the socio-economic impact, human systematic innovation helix, knowledge management skills, socio-emotional skills, and business skills of executives. Companies. This effort has increased understanding of the influence of delayed or postponed action on your business growth decisions. Bright Institute 2022-07-02 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/42 10.47738/ijaim.v2i4.42 International Journal for Applied Information Management; Vol. 2 No. 4 (2022): Regular Issue: December 2022; 95-105 2776-8007 10.47738/ijaim.v2i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/42/45 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/43 2025-12-30T17:03:25Z ijaim:ART

The Legal System for the Conversion of Commercial Companies in the Light of the Rules of the Saudi Corporate System Alomari, Mohammad S. Saudi Arabia Vision 2030 Company Law Openness Conversion Transformation As Saudi Arabia gears towards economic advancement and openness, in line with its vision 2030, there is need to have a suitable business environment that is favorable for commercial companies to thrive and create more job opportunities for the population. One way to achieve this, is by ensuring that there is a proper legal framework that allows for the conversion of commercial companies from one form to another, which suits the country’s economic ambitions. This thus enables commercial companies to convert into legal structures that can adapt in the changing environment and ensure that they contribute greatly to Saudi Arabia’s economy. Commercial companies that may have initially been operating via forms that rendered them ineffective, can convert into forms that allows them to operate efficiently and ensure that they have a strong and competitive position in the market while not necessarily changing their legal structures. This research paper thus examines and critically analyses the legal framework in Saudi Arabia that governs the conversion of commercial companies as enshrined under the Saudi Arabia Company Law. This research paper aims to establish that a suitable legal system for the conversion of commercial companies in Saudi Arabia is crucial for the economic growth of the country. Bright Institute 2022-08-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/43 10.47738/ijaim.v2i4.43 International Journal for Applied Information Management; Vol. 2 No. 4 (2022): Regular Issue: December 2022; 106-111 2776-8007 10.47738/ijaim.v2i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/43/46 Copyright (c) 2022 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/46 2025-11-21T05:13:05Z ijaim:ART

A Summary of Relay Protection-based Simulation for Dynamic Performance and Reliability Assessment Li, Fei Zhuyuan, Luochen Relay Protection Reliability Dynamic Performance As technology advances, electricity has become an essential aspect of both national security and daily life. Ensuring the safety of the power grid is thus of utmost importance. However, in China, research on relay protection models for dynamic simulation of power systems is still in its early stages. Due to this, the control laws of relay protection elements have not been well understood, leading to inadequate handling of system failures. To ensure the safe operation of power systems, it is crucial to first strengthen the grid structure of the power system. This can be achieved through the improvement of elasticity coefficient, reasonable distribution of reserve capacity, and the reinforcement of the adjustment ability of the tie line between major power grids. Additionally, improving the stable reserve of the power grid is essential. To improve the authenticity and reliability of dynamic simulation, it is necessary to establish a set of relay protection models that are consistent with actual relay protection. By doing so, the stability problem in the power system can be accurately analyzed, leading to improved reliability. In this study, a relay protection model was established that reduces the complexity of modeling and can accurately reflect the dynamic characteristics of the power system following interference. This model is significant to the analysis and research of power systems, as it can enhance the understanding of control laws for relay protection elements, leading to improved management of system failures and better overall reliability. Bright Institute 2023-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/46 10.47738/ijaim.v3i1.46 International Journal for Applied Information Management; Vol. 3 No. 1 (2023): Regular Issue: April 2023; 11-23 2776-8007 10.47738/ijaim.v3i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/46/48 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/47 2025-11-21T05:13:05Z ijaim:ART

Exploring the Implementation of Multimedia Technology in Contemporary Home Product Design for Regional Culture Inheritance and Innovation Sheng, Kang Multimedia Technology Regional Culture Modern Home Products Heritage and Innovation In recent years, the design market in China for household products has seen a surge in scale and speed. This shift has taken place from a decoration market to a design market. There is now a wide range of styles available for modern home product designs, with Western design styles becoming increasingly popular. However, it has been noticed that some domestic designers have followed the principles of modernism, minimalism, and high-techism, and this has resulted in many designs being created by simple copying of computer-generated designs, without much thought. This approach has led to the loss of the individuality of modern home product design styles. A modern household product design with an elegant taste and extraordinary style is not solely dependent on how much money is spent and how many high-grade decorative materials are used. It is important to combine regional culture with the appropriate use of the elements of modern household product design. It is also essential to create a fully functional, beautiful, generous, and elegant style for indoor environments with limited room space. Regional modern household product design refers to the combination of the local natural environment and cultural environment. It emphasizes local characteristics and national style, and the nationalization of modern household product design and creation tendency. In the design process, local materials and practices should be used as much as possible to display the characteristics of local conditions and merge the overall style with the local environment. To achieve this goal, it is essential to consider the region fully. Regional modern household product design can create a unique and individual design style. The use of local materials and practices will enable the design to reflect the characteristics of the local environment, resulting in a cohesive style. The use of regional culture and local elements will make the design more attractive to potential customers. Therefore, it is necessary to focus on creating a unique style of modern household product design, which combines regional culture with modern design elements. Bright Institute 2023-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/47 10.47738/ijaim.v3i1.47 International Journal for Applied Information Management; Vol. 3 No. 1 (2023): Regular Issue: April 2023; 24-32 2776-8007 10.47738/ijaim.v3i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/47/49 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/50 2025-11-21T05:13:05Z ijaim:ART

Predicting Customer Churn: Revolutionizing Retail with Machine Learning Jung, Sun Kyoung Tsang, Seng-Su Phumchusri, Naragain Data Technology Tree Data Processing Computer Software Engineering The ultimate objective of every business is to increase sales and profits. When a company's regular customers suddenly stop buying from them, it can cause a significant decrease in revenue. It is a widely accepted fact that retaining existing customers is less expensive than acquiring new ones, which is why Customer Relationship Management (CRM) places a high emphasis on it, particularly in the retail industry. When a customer stops shopping at a store, the business loses the opportunity to make more sales and even cross-sell. Therefore, companies must identify customers who are at risk of leaving and take preventative measures to retain them. This article highlights the effectiveness of using machine learning in conjunction with transaction data for predicting customer churn in the retail industry. The study involved 5,115,472 customer loyalty card records from a European retailer's data warehouse, which were utilized to train the machine learning models. The results showed that machine learning models outperformed their linear regression counterparts. Bright Institute 2023-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/50 10.47738/ijaim.v3i1.50 International Journal for Applied Information Management; Vol. 3 No. 1 (2023): Regular Issue: April 2023; 46-57 2776-8007 10.47738/ijaim.v3i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/50/51 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/51 2025-11-21T05:13:05Z ijaim:ART

Using Information Technology to Quantitatively Evaluate and Prevent Cybersecurity Threats in a Hierarchical Manner Mai, Rui Wu, Mingzhu Information Technology Network Security Threat Situation Hierarchical Network Quantitative Assessment Security Precautions The vulnerability of traditional network security technology in the face of rapid advancements in information technology and the constant changes in network security. As a result, hackers can easily exploit loopholes in traditional security measures, such as cracking cryptographic algorithms, and stealing sensitive user information and data, which has led to a crisis of trust in recent years. To ensure safe and effective operation of massive data on the network, this article presents a quantitative assessment of the network's threat situation. The assessment is divided into two parts: support evaluation and credibility evaluation. These parts are further broken down into three levels of evaluation and severity evaluation. The article also provides a list of network security-related precautions that can be taken to mitigate potential risks. The experimental results show that implementing these hierarchical security measures can improve the security rate of Internet users' information by 4%-5%. Overall, the article highlights the importance of adopting more advanced and sophisticated security measures to combat the increasingly complex threats posed by cybercriminals. Bright Institute 2023-04-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/51 10.47738/ijaim.v3i1.51 International Journal for Applied Information Management; Vol. 3 No. 1 (2023): Regular Issue: April 2023; 01-10 2776-8007 10.47738/ijaim.v3i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/51/47 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/52 2025-11-21T05:33:21Z ijaim:ART

Optimizing Supply Chain Coordination through Cross-Functional Integration: A Dynamic Model Using Optimal Control Theory Al-Matar, Najeeb AlMatar , Mufeed Tadj, Lotfi Dynamic Demand Optimal Control Product Deterioration Raw Material Deterioration Supplier Relationship Management This paper is concerned with the cross-functional coordination of certain internal and external processes in a supply chain to balance supply with customer demand. Activities need to be synchronized in order to avoid issues such as delays in delivery and unnecessary inventory of raw material or of finished products. This can be achieved by integrating the purchasing, logistics, and production processes together. We propose a dynamic model and employ optimal control theory to obtain the optimal raw material supply rate, the optimal transfer rate of the raw material for production, and the optimal production rate. Some managerial insights are obtained through numerical examples and sensitivity analyses. Among the insights gained is that the approach is well suited for medium to long range planning horizon, when raw material and end product deterioration are high, and when the initial gaps between the inventory levels and their respective goals are the smallest. Bright Institute 2023-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/52 10.47738/ijaim.v3i2.52 International Journal for Applied Information Management; Vol. 3 No. 2 (2023): Regular Issue: July 2023; 70-81 2776-8007 10.47738/ijaim.v3i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/52/53 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/53 2025-11-21T05:33:21Z ijaim:ART

Investigation into the Application of Image Modeling Technology in the Field of Computer Graphics Doungmala, Pathasu Thai, Thanh Hai Image Modeling Tech Computer Graphics Hidden Algorithm The field of computer graphics has experienced remarkable advancements in hardware and software, leading to rapid progress and development. One crucial aspect that significantly influences the authenticity and immersive nature of simulation environments is the utilization of image modeling technology. The success of creating realistic and captivating image modeling environments relies heavily on the effective implementation of this technology. In light of this, the present paper thoroughly examines the fundamental concepts of computer graphics and image modeling technology. Furthermore, it delves into an in-depth analysis of the integration of image modeling technology within the domain of computer graphics, followed by an exploration of the concealed algorithm behind its functioning. The continuous evolution of computer graphics systems, encompassing advancements in both hardware and software, has propelled the field forward at a remarkable pace. Among the various elements that contribute to the credibility and engagement of simulation environments, the utilization of image modeling technology stands out as a critical factor. This research paper endeavors to comprehensively investigate the fundamental principles of computer graphics and the intricate workings of image modeling technology. By dissecting and analyzing the conceptual framework of computer graphics and image modeling, the study sheds light on their interplay and interdependence. Finally, the paper unveils the concealed algorithm that underlies the operation of image modeling technology within the realm of computer graphics, thereby providing valuable insights into its inner workings. Bright Institute 2023-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/53 10.47738/ijaim.v3i2.53 International Journal for Applied Information Management; Vol. 3 No. 2 (2023): Regular Issue: July 2023; 82-90 2776-8007 10.47738/ijaim.v3i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/53/54 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/54 2025-11-21T05:33:21Z ijaim:ART

Development of an IoT-Based Parking Space Management System Design Wang, Ange Qin, Zhengtao Internet of Things Parking Management TechIO System Design With the improvement of people's quality of life and the rapid development of the automobile consumer market, the problem of urban parking difficulties has become increasingly prominent. In addition to the insufficiency of the number of supporting parking spaces, the backwardness of the traditional parking lot operation model has led to insufficient openness and transparency of various information, which limits the ability of drivers to obtain parking space information, and limited parking spaces cannot be adequately obtained. Utilization is also one of the reasons for the increasing difficulty of urban parking. This article aims to study the design of parking space management system based on Internet of Things technology, choose TechIO technology to realize wireless communication between parking spaces in the parking lot, analyze the advantages of TechIO technology and the needs of parking space management system, and build a simulation based on the system design the test environment has made relevant tests on the various items of the system. The test results show that the use of TechIO technology makes the system have the characteristics of strong adaptability, low cost, and low power consumption, which not only eliminates the complicated wiring costs in the parking lot, but also brings great convenience to the deployment of parking lot nodes. Bright Institute 2023-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/54 10.47738/ijaim.v3i2.54 International Journal for Applied Information Management; Vol. 3 No. 2 (2023): Regular Issue: July 2023; 91-100 2776-8007 10.47738/ijaim.v3i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/54/55 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/55 2025-11-21T05:33:21Z ijaim:ART

Developing a Predictive Information System for Determining the Prognosis of HIV and Tuberculosis Co-Infection in Incarcerated Individuals Lai, Jingzhen The research describes the development of the forecasting information system that can predict the outcome of a disease in inmates with HIV-associated tuberculosis. The aim of the research is to develop an additional high-precision diagnostic criterion giving the possibility of the timely correction of diagnostic, treatment and organizational measures for patients with HIV and tuberculosis co-infection that helps to improve the quality of medical care. The research material is based on the data from clinical cases of patients with HIV and tuberculosis co-infection who were hospitalized in a tuberculosis hospital providing specialized medical care to inmates from 2012 to 2018. (367 people). The study methodology was developed in several stages with the use of the methods of system analysis and mathematical modeling (logical-statistical method of optimally reliable partitions, the method of analysis of hierarchies, artificial neural network, methods of statistical grouping). The result of a complex multi-stage research makes possible the development of the prognostic index forecasting outcome of HIV-associated tuberculosis in prisoners. For the automated calculation of the developed index a software package was created. Interpretation of the received data allows timely correcting of diagnostic and treatment tactics in order to improve the quality of medical care and reduce the hospital mortality rate. The developed information system does not require complex and expensive diagnostic measures, it is easy to use and can be suggested to use as a screening method. Bright Institute 2023-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/55 10.47738/ijaim.v3i2.55 International Journal for Applied Information Management; Vol. 3 No. 2 (2023): Regular Issue: July 2023; 101-110 2776-8007 10.47738/ijaim.v3i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/55/56 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/56 2025-11-21T05:33:21Z ijaim:ART

Design and Development of Intelligent Logistics Tracking System Based on Computer Algorithm Dong, Demei Gao Intelligent Logistics Computer Algorithm Decision Support System The logistics industry has experienced significant growth alongside the progress of the social economy. In this research article, the aim is to create a sophisticated tracking system for the logistics sector by utilizing computer technology. The primary focus is on developing an intelligent inventory decision support system. The article introduces two key algorithms: one that detects the integrity of goods packaging and another that identifies the behavior and posture of goods using a three-dimensional acceleration sensor. Furthermore, the article describes the workflow of the system and provides a thorough design for implementation in a real cabin environment. To validate the effectiveness of the system, experiments are conducted, and its performance is evaluated. The continuous advancement of the logistics industry, driven by the growth of the social economy, has prompted the need for innovative solutions. This scholarly article aims to address this demand by proposing the development of an intelligent logistics tracking system empowered by computer technology. The primary objective is to create an intelligent inventory decision support system capable of optimizing inventory management processes. To achieve this, the article presents two crucial detection algorithms. The first algorithm focuses on assessing the integrity of goods packaging, ensuring that goods remain intact throughout the logistics journey. The second algorithm leverages a three-dimensional acceleration sensor to analyze the behavior and posture of goods during transportation. The article also provides a comprehensive overview of the system's workflow, detailing the various steps involved. Furthermore, to validate the practical applicability and efficiency of the system, a detailed design is executed in a real cabin environment. Through rigorous experimentation and performance evaluation, the article aims to ascertain the effectiveness of the proposed system in enhancing logistics operations. Bright Institute 2023-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/56 10.47738/ijaim.v3i2.56 International Journal for Applied Information Management; Vol. 3 No. 2 (2023): Regular Issue: July 2023; 58-69 2776-8007 10.47738/ijaim.v3i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/56/52 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/57 2025-11-21T05:09:44Z ijaim:ART

Formulation and Implementation of a Bayesian Network-Based Model Shi, Ying Bayesian Network Structure Learning Parameter Learning Knowledge Reasoning Genetic At present, Bayesian networks lack consistent algorithms that support structure establishment, parameter learning, and knowledge reasoning, making it impossible to connect knowledge establishment and application processes. In view of this situation, by designing a genetic algorithm coding method suitable for Bayesian network learning, crossover and mutation operators with adjustment strategies, the fitness function for reasoning error feedback can be carried out. Experimental results show that the new algorithm not only simultaneously optimizes the network structure and parameters, but also can adaptively learn and correct inference errors, and has a more satisfactory knowledge inference accuracy rate. Bright Institute 2023-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/57 10.47738/ijaim.v3i3.57 International Journal for Applied Information Management; Vol. 3 No. 3 (2023): Regular Issue: September 2023; 101 - 108 2776-8007 10.47738/ijaim.v3i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/57/57 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/58 2025-11-21T05:09:44Z ijaim:ART

Exploration of an "Internet+" Grounded Approach for Establishing a Model for Evaluating Financial Management Risks in Enterprises Wang, Hongli Budsaratragoon, Pornanong Internet Financial Management System Risk Evaluation With the rapid development and continuous updating of computing technology, computer software is increasingly used in various management of enterprises, which brings great aspects to enterprise management and also creates high benefits for enterprises. This article takes the hospital as an example, based on Internet technology, evaluates the risks of the hospital financial management system, and establishes the relevant risk evaluation model according to the relevant elements of the medical financial management system. In the normal use of the hospital financial management ERP business, the risk consequences are formed through probability calculations. The evaluation value, and finally the evaluation value of the risk of the ERP project of the hospital financial management is calculated. The experimental results show that the average error between the evaluation results of the model and the actual financial value is only 2.429%, indicating that this evaluation method is highly accurate and has strong applicability. Bright Institute 2023-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/58 10.47738/ijaim.v3i3.58 International Journal for Applied Information Management; Vol. 3 No. 3 (2023): Regular Issue: September 2023; 109 - 117 2776-8007 10.47738/ijaim.v3i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/58/58 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/59 2025-11-21T05:09:44Z ijaim:ART

Development of a Model for Recognizing Cracks on Concrete Surfaces Using Digital Image Processing Techniques Kang, Yuzhong Yu, Aimin Zeng, Wenquan Concrete Bridge Crack Detection Digital Image Computer Identification Image Processing In this paper, the bridge crack detection method based on digital images is studied. In-depth analysis and evaluation are performed on the image processing algorithms such as image graying, resolution of checkerboard corner pixel rate, filtering denoising, and edge detection, etc. The calculation and software system for bridge crack width based on videos (or images) is implemented, and 15 bridge crack images are used to verify its crack detection accuracy. The results suggest that the proposed crack identification method in this paper can be used for the crack detection of reinforced concrete bridges and class B prestressed concrete bridges properly. When the crack width is greater than 0.3 mm, the calculated crack width value based on images is very close to the measured value. Bright Institute 2023-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/59 10.47738/ijaim.v3i3.59 International Journal for Applied Information Management; Vol. 3 No. 3 (2023): Regular Issue: September 2023; 118 - 124 2776-8007 10.47738/ijaim.v3i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/59/59 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/60 2025-11-21T05:09:44Z ijaim:ART

Examination of the Global Plant Factory's National Competitiveness via Artificial Intelligence-Driven Research Analysis Wang, Feng Park, Jae-Hoon Plant Industrialization Situation Analysis National Competitiveness The plant factory is an advanced stage of the development of modern facility agriculture. It integrates biotechnology, engineering technology and system management to free agricultural production from the constraints of natural ecology and other objective conditions. A factory agricultural system that produces production according to human plans. Plant factories are one of the most dynamic and potential fields in the process of absorbing and applying high-tech achievements in the process of agricultural industrialization, and have attracted more and more attention from countries. This paper uses the SCI-EXPANDED database of Web of Science as the data source, adopts bibliometric methods, and focuses on the analysis of the competitiveness of various countries in the field of plant factory research in the world, providing information support and data reference for related. Bright Institute 2023-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/60 10.47738/ijaim.v3i3.60 International Journal for Applied Information Management; Vol. 3 No. 3 (2023): Regular Issue: September 2023; 125 - 133 2776-8007 10.47738/ijaim.v3i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/60/60 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/61 2025-11-21T05:09:44Z ijaim:ART

Creation and Investigation of a Big Data Technology-Driven Auxiliary Employment Platform for Public Utilities Management Lan, Zhijie Big Data Public Utilities Management Employment Platforms With the development of society and the advancement of science and technology, the current employment problem has gradually become hotter. At the same time, the number of college graduates has shown rapid growth. However, due to the development of science and technology in our country, the demand for labor has declined, and various factors have caused college students to find themselves in a difficult situation.The purpose of this article is to conduct research on the design of a public utility management assisted employment platform based on big data technology. Based on the analysis of the employment history and current situation of college students in New China, this paper analyzes the employment dilemma of college students from the perspective of "New Public Management", applies the concept of new public management to the public service platform of college student employment, and proposes that college students should be further improved. The degree of marketization of employment, the construction of a diversified employment service platform for college students, etc.Further clarify the focus of solving the employment problem of college students. Due to the theoretical and practical deficiencies of the new public management itself, the employment platform for college students derived from the perspective of the new public management has deficiencies. The experimental research results show that the effectiveness of the auxiliary employment platform for public utilities management is better is the auxiliary employment platform C for public utilities management, with an effectiveness of 75.83%. In general, the effective average of the auxiliary employment platform for public utilities management is 70. It can be seen that the actual use of these auxiliary employment platforms is not large, and at the same time, it also shows that there is a lot of room for. Bright Institute 2023-09-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/61 10.47738/ijaim.v3i3.61 International Journal for Applied Information Management; Vol. 3 No. 3 (2023): Regular Issue: September 2023; 134 - 141 2776-8007 10.47738/ijaim.v3i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/61/61 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/62 2025-11-21T04:52:25Z ijaim:ART

Design and Development of Product Sales Website Using the Waterfall Methodology: An Academic Approach Megananda, Evelyn Gina Khairunisa, Fitria Is’aaf Fadillah, Septiya Nur Ali, Siti Saekhah Tarwoto Website Development Waterfall The development of digital technology and the internet has significantly changed the business landscape, especially in terms of product marketing and promotion. One area that has been significantly affected is the MSME (Micro, Small, and Medium Enterprises) industry. MSMEs often face challenges in expanding their market and increasing their revenue due to limited resources and limited accessibility. The existence of a website can make it easier for business actors to promote their products in order to reach wider marketing and make it easier and faster for consumers to find product information provided by business owners. The purpose of this research is to create a marketing website using a Waterfall with the help of WordPress software. Bright Institute 2023-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/62 10.47738/ijaim.v3i4.62 International Journal for Applied Information Management; Vol. 3 No. 4 (2023): Regular Issue: Desember 2023; 142-153 2776-8007 10.47738/ijaim.v3i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/62/62 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/64 2025-11-21T04:52:25Z ijaim:ART

Soft Sensing Image Analysis and Processing Method of Substation Equipment Defects Banihashemi, Saeed Zhang, Jingxiao Substation Equipment Commisioning Management Measurement In the context of incentivizing regulation for distribution companies, the utilization of a reference network model proves to be a valuable tool for evaluating their effective cost. These models play a crucial role in planning expansive distribution areas that encompass various voltage levels. This paper introduces a green space planning algorithm designed to optimize the location, size, and power supply areas of medium and low voltage substations within the Reference Network Model (RNM). The algorithm aims to enhance the efficiency and environmental impact of these substations. The focus of this study extends to two key aspects: the creation of "environment-friendly" substations and the significance of implementing "resource-saving" substations in China. The evaluation of "environment-friendly" and "resource-saving" characteristics is conducted through comprehensive analysis, with results indicating notable features. Feature 1, associated with environmental friendliness, is measured at 0.363, while Feature 2, emphasizing resource-saving attributes, achieves a high score of 0.835. Furthermore, Feature 3, addressing the importance of implementing these eco-friendly substations in the Chinese context, attains a commendable score of 0.824. The findings underscore the potential of the proposed green space planning algorithm in enhancing the sustainability and efficiency of medium and low voltage substations within the incentive regulation framework for distribution companies. Bright Institute 2023-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/64 10.47738/ijaim.v3i4.64 International Journal for Applied Information Management; Vol. 3 No. 4 (2023): Regular Issue: Desember 2023; 154-161 2776-8007 10.47738/ijaim.v3i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/64/63 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/65 2025-11-21T04:52:25Z ijaim:ART

Optimization of Data Encryption Technology in Computer Network Communication Lin, Jun Shen, Zhiqi Computer Network Communication Data Encryption In recent years, the pervasive integration of computer network communication systems across various industrial domains has revolutionized daily life and work, offering unprecedented convenience. Recognizing the paramount importance of securing these communication channels, this paper meticulously examines the current landscape and distinctive features of data encryption technology in computer network communication security. To comprehend the evolving threat landscape, the paper elucidates prevalent security challenges confronting contemporary networks. Subsequently, the study delves into a comprehensive discussion on the implementation of data encryption technology to fortify network communication security. This includes a nuanced exploration of link encryption technology, node encryption technology, and end-to-end encryption technology, elucidating their respective roles and effectiveness. Moreover, the paper undertakes a profound analysis of the practical application of data encryption technology within the realm of computer network communication security. Employing empirical evidence, the study reveals significant findings, such as the Mean Squared Error (MSE) values for data sets. Specifically, the MSE value for data 1 is recorded at 42.453, data 2 at 87.324, and data 3 at 87.324674. These findings provide invaluable insights into the performance and efficacy of data encryption technology in safeguarding computer network communications, paving the way for enhanced security measures in the dynamic and ever-expanding digital landscape. Bright Institute 2023-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/65 10.47738/ijaim.v3i4.65 International Journal for Applied Information Management; Vol. 3 No. 4 (2023): Regular Issue: Desember 2023; 162-169 2776-8007 10.47738/ijaim.v3i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/65/64 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/66 2025-11-21T04:52:25Z ijaim:ART

Design of Medical Diagnostic System Based on Artificial Intelligence Wang, Yu-Hui Lin, Guan-Yu Artificial Intelligence Phase-Changing Algorithms Medical Diagnostic Systems System Updates With the progress of science and technology, material life is getting better and better now, so people have begun to have higher and higher requirements for life and longevity has more and more yearning. In ancient times are through artificial diagnosis to find out the physical condition, Chinese medicine is expected to smell cut the four major methods of diagnosis and treatment, but can achieve this skill only a small number of people, and most of the disease can not be identified, not good to treat patients. So now with the progress of science and technology, technology and intelligent rapid development, artificial intelligence may be able to make some contributions to the diagnosis of the disease. Therefore, the purpose of this paper is to design artificial intelligence-based medical diagnostic system to update. In this paper, after identifying the basic structure of artificial intelligence and constructing the database, we understand the diagnosis methods of medical diagnostic system and other diagnostic systems, and finally, the medical diagnostic system can be updated by using the phase-changing algorithm, so that it can better fit with artificial intelligence, so as to ensure the success rate of treatment and the correct rate of diagnosis. Experimental results show that the use of artificial intelligence as a basis for medical diagnostic systems can better identify the disease and make complementary treatment options. Bright Institute 2023-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/66 10.47738/ijaim.v3i4.66 International Journal for Applied Information Management; Vol. 3 No. 4 (2023): Regular Issue: Desember 2023; 170-176 2776-8007 10.47738/ijaim.v3i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/66/65 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/67 2025-11-21T04:52:25Z ijaim:ART

Analysis of the Implementation of ITIL V3 Domain Service Operation in Enhancing the Quality of Information Technology Services Fauzan, Kiagus Rachmat Nurdianto, Imam Bayu Muhammad, Yudhistira Santosa, Muhammad Wildan Prakoso, Osara Gandang Wijanarko, Aris Tarwoto Information Technology ITIL V3 Service Operation The rapid growth in the hotel industry in Purwokerto has given rise to new challenges related to the management and provision of information technology services. In the midst of increasingly fierce competition, the success of a hotel depends not only on the quality of service but also on the effectiveness of the information technology systems that support its operations. To overcome this complexity, Hotel ABC Purwokerto has adopted the ITIL V3 Domain Service Operation approach in managing its information technology services. This article aims to provide comprehensive insight into how hotels can optimize their operations through effective information technology service management. The use of the ITIL V3 Domain Service Operation framework at Hotel ABC is not only a solution to respond to rapid changes in information technology but also an effort to meet the high expectations of guests who are increasingly smart and technology-savvy. Through careful analysis, this article will reveal how implementing ITIL V3 at the operational level can have a positive impact on the efficiency, reliability and innovation of information technology services provided by Hotel ABC. By understanding the context and problems faced by Hotel ABC Purwokerto, we can explore in more depth how ITIL V3-based information technology service management strategies can be the key to success in improving service quality and maintaining competitiveness in this dynamic hotel industry. Bright Institute 2023-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/67 10.47738/ijaim.v3i4.67 International Journal for Applied Information Management; Vol. 3 No. 4 (2023): Regular Issue: Desember 2023; 177-183 2776-8007 10.47738/ijaim.v3i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/67/66 Copyright (c) 2023 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/70 2025-11-21T05:46:02Z ijaim:ART

Risk Management in Information Systems: Applying ISO 31000:2018 and ISO/IEC 27001:2022 Controls at PMI's Central Clinic Basri, Wahyu Setiawan Ayu, Adinda Laras PMI Risk Management Information System ISO 31000:2018 ISO 27001:2022 PMI Main Clinic is a national association organization in Indonesia engaged in health services. PMI Main Clinic has an information system to support its health service process. One of the information systems is the Clinic Management Information System (Smart Klinik), this information system is used to record patients from the beginning of the patient's arrival to register until the patient gets the medicine. PMI Main Clinic has never implemented information system risk management before. If a risk occurs at the PMI Main Clinic, the PMI Main Clinic can suffer huge losses and hamper the health service process. To find out the possible risks that can occur at PMI, the ISO 31000: 2018 method is used and the control standard uses ISO 27001: 2022. It can be seen from the 22 possible risks, there are 4 possible risks with very high levels, 2 possible risks with high risk levels, 10 possible risks with moderate risk levels, and 6 possible risks with low risk levels. The control recommendations used ISO/EIC 27001:2022 from the result Equipment maintenance, Information backup, Protection against malware, Installation of software on operational systems, Monitoring activities, Web filtering, Network’s security, Security of network services, Segregation of networks, Secure system architecture and engineering principles. Bright Institute 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/70 10.47738/ijaim.v4i1.70 International Journal for Applied Information Management; Vol. 4 No. 1 (2024): Regular Issue: April 2024; 1-13 2776-8007 10.47738/ijaim.v4i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/70/67 Copyright (c) 2024 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/71 2025-11-21T05:46:02Z ijaim:ART

Utilizing Analytical Hierarchy Process (AHP) in Developing Decision Support System for Evaluating Teacher Performance Prasetyo, Doni Marodiyah, Inggit Teacher Performance Assessment Decision Support System AHP One effort to measure the quality level in schools is by assessing the performance aspects of teachers as professional educators teaching in those schools. The performance aspect of teachers is measured as one of the requirements for promotion to higher positions or as a prerequisite recommendation to participate in teacher certification activities. In order for teacher performance assessment to be conducted objectively, a method that can assist in the process is required. The Analytical Hierarchy Process (AHP) method can be used to aid in decision-making. This is because the AHP method is a model for structured and comprehensive decision-making. Data from the Analytical Hierarchy Process calculation were obtained from 5 questionnaires filled out by respondents, and the final result obtained was C with a superior weight of 0.7604 or 76.04%, the second priority was obtained by B with a weight value of 0.2079 or 20.79%, and the lowest priority was obtained by A with a weight value of 0.0517 or 5.17%. Bright Institute 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/71 10.47738/ijaim.v4i1.71 International Journal for Applied Information Management; Vol. 4 No. 1 (2024): Regular Issue: April 2024; 14-21 2776-8007 10.47738/ijaim.v4i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/71/68 Copyright (c) 2024 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/72 2025-11-21T05:46:02Z ijaim:ART

Uncovering the Efficiency of Phishing Detection: An In-depth Comparative Examination of Classification Algorithms Sugianto, Dwi Putawa, Rilliandi Arindra Izumi, Calvina Ghaffar, Soeltan Abdul Phishing email attacks Classification algorithms XGBoost model Email security Cross-validation This research aims to investigate the potential security risks associated with phishing email attacks and compare the performance of three main classification algorithms: random forest, SVM, and a combination of k-fold cross-validation with the xgboost model. The dataset consists of 18,634 emails, with 7,312 identified as phishing emails and 11,322 considered safe. Through experiments, the combination of k-fold cross-validation and xgboost demonstrated the best performance with the highest accuracy of 0.9712828770799785. The email classification graph provides a visual insight into the distribution of classification results, aiding in understanding patterns and trends in phishing attack detection. The analysis of the ROC curve results indicates that k-fold cross-validation and xgboost have a higher AUC compared to random forest and SVM, signifying a better ability to predict the correct class. The conclusion emphasizes the importance of the combination of k-fold cross-validation and xgboost in enhancing email security, with the potential for increased accuracy through parameter adjustments. Bright Institute 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/72 10.47738/ijaim.v4i1.72 International Journal for Applied Information Management; Vol. 4 No. 1 (2024): Regular Issue: April 2024; 22-29 2776-8007 10.47738/ijaim.v4i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/72/69 Copyright (c) 2024 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/73 2025-11-21T05:46:02Z ijaim:ART

Assessing Ticket.com App Usability Through the System Usability Scale (SUS) Method Putri, Shiffa Intania Liu, Kevin Usability Scale (SUS) Usability Evaluation The influence of technology has increased ease and comfort, especially in the online ticket ordering process. One of the online ticket booking platforms that is popular among users is Tiket.com. However, on the Tiket.com application, there are still various negative reviews given by users. One way to maintain an application is to pay attention to usability aspects, especially user input. So, this research aims to evaluate the Tiket.com application in terms of usability using the System Usability Scale (SUS) method as a data processing method. The results obtained from calculating the SUS score in usability evaluation were 55.55. This score shows that the usability level of the Tiket.com application is quite good, with the Adjective Ranking being in the OK category, and Acceptable at Marginal level and Grade D level. Even though the assessment results are acceptable, there are various things that need to be considered, including increasing the use of features. to function properly and pay attention to every user input. This is done so that it can have a significant impact on the Tiket.com application, especially in improving the usability aspect. Bright Institute 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/73 10.47738/ijaim.v4i1.73 International Journal for Applied Information Management; Vol. 4 No. 1 (2024): Regular Issue: April 2024; 30-40 2776-8007 10.47738/ijaim.v4i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/73/70 Copyright (c) 2024 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/74 2025-11-21T05:46:02Z ijaim:ART

Navigating English Learning via Heutagogical Approaches in Self-Directed Learning with Technology Xuan, Zhicheng Dai Xhu, Xiaoliang Self-Directed Learning Technology Heutagogy English Language Learning Technology has created a demand for new learning methods in education, such as e-learning, blended learning, and flipped learning. Self-directed is one of the new learning approaches that functions primarily based on technological learning mediums. With the advent of technology, present-day learners can access several new learning mediums that expose them to language learning resources. This accessibility motivates the learners to choose the content, manage their learning activities, and assess what they learn with the support of technology. This study designs a tech-driven teaching-learning methodology by blending SDL with heutagogy and further aims to discover how much technological learning mediums help students in SDL. It also emphasizes the role of technology in developing SDL as a heutagogical approach to learning several components of the English language. A survey was conducted among the first-year engineering students of Anna University to collect data on using learning media in SDL regarding English Language Learning. Findings reveal that most students prefer technological learning mediums to learning by themselves. It also leads to the recommendation that students create awareness about SDL as a learning system that will help them promote self-paced learning. Bright Institute 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/74 10.47738/ijaim.v4i1.74 International Journal for Applied Information Management; Vol. 4 No. 1 (2024): Regular Issue: April 2024; 41-53 2776-8007 10.47738/ijaim.v4i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/74/71 Copyright (c) 2024 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/79 2025-11-21T05:43:37Z ijaim:ART

Job Clustering Based on AI Adoption and Automation Risk Levels: An Analysis Using the K-Means Algorithm in the Technology and Entertainment Industries Hasibuan, Muhammad Siad Fikri, Ruki Rizal Nul Dewi, Deshinta Arrova AI Adoption Automation Risk K-Means Clustering Workforce Planning Technology and Entertainment Industries This study explores job clustering based on AI adoption levels and automation risks in the technology and entertainment industries using the K-Means algorithm. By applying K-Means clustering, jobs were grouped into five clusters based on their AI adoption and susceptibility to automation. The analysis revealed that Cluster 1, with roles such as software engineers and data scientists, exhibited higher AI adoption and lower automation risks, making these positions more resilient to automation. In contrast, other clusters reflected varying degrees of AI integration and automation vulnerability, offering insights into workforce trends. Principal Component Analysis (PCA) and a heatmap of salary distributions further highlighted the economic implications of these clusters, with Cluster 3 representing the highest-paying roles. The findings suggest the importance of tailored upskilling and reskilling strategies to address the challenges of workforce displacement in AI-driven environments. This study provides actionable insights for workforce planning in industries facing rapid technological transformation. Bright Institute 2024-07-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/79 10.47738/ijaim.v4i2.79 International Journal for Applied Information Management; Vol. 4 No. 2 (2024): Regular Issue: July 2024 2776-8007 10.47738/ijaim.v4i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/79/72 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/80 2025-11-21T05:43:37Z ijaim:ART

Sentiment Analysis of Doctor’s Responses to Patient Inquiries in a Medical Chatbot: A Logistic Regression Approach Yel, Mesra Betty Rodhiyah Sentiment Analysis Medical Chatbot Logistic Regression Doctor-Patient This study addresses the challenge of improving doctor-patient communication in medical chatbot systems by integrating sentiment analysis to classify doctor responses as positive or negative. The primary objective was to develop a model that enhances the emotional intelligence and appropriateness of chatbot interactions using Logistic Regression. The model achieved 98.63% accuracy, 99.68% precision, 95.90% recall, and 97.75% F1-score, demonstrating its high reliability in classifying sentiments with minimal misclassifications. While the model performs well, further improvements could focus on reducing false negatives to increase recall. The implications of this research are significant for digital healthcare, as the model enables chatbots to provide more empathetic, context-aware responses, improving patient engagement and overall communication. The novelty of this study lies in applying sentiment analysis within medical chatbot systems, contributing to the growing field of emotional intelligence in digital healthcare. The findings highlight the potential of sentiment analysis to enhance patient interactions, making medical chatbots more effective and human-like. This study provides a solid foundation for further advancements in healthcare chatbots, demonstrating the potential of machine learning to improve the quality of doctor-patient communication in a digital context. Bright Institute 2024-07-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/80 10.47738/ijaim.v4i2.80 International Journal for Applied Information Management; Vol. 4 No. 2 (2024): Regular Issue: July 2024 2776-8007 10.47738/ijaim.v4i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/80/73 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/81 2025-11-21T05:43:37Z ijaim:ART

Using Random Forest and Support Vector Machine Algorithms to Predict Online Shopper Purchase Intention from E-Commerce Session Data Alamsyah, Reza Wahyuni, Sri Online Shopper Behavior Machine Learning Random Forest Purchase Intention E-commerce This study explores the use of machine learning algorithms to predict online shopper purchase intention, aiming to provide e-commerce businesses with actionable insights into consumer behavior. The Online Shoppers Purchasing Intention dataset, containing 12,330 session records from an e-commerce site, was analyzed using two classification models: Random Forest and Support Vector Machine (SVM). The models were evaluated based on key performance metrics including accuracy, precision, recall, F1-score, and ROC AUC. Results showed that the Random Forest model outperformed the SVM model, achieving an accuracy of 90.43% and a ROC AUC score of 0.94, indicating strong predictive capability. PageValues and ProductRelated_Duration were identified as the most important features influencing purchasing behavior, with higher values of these features being strongly associated with successful purchases. The study provides valuable insights into the behaviors that drive purchasing decisions in e-commerce, showing that longer engagement with product-related content and higher monetary value pages significantly increase the likelihood of conversion. While the study contributes to understanding online shopper behavior through machine learning, it is limited by the class imbalance in the dataset and the absence of more granular customer data. Future research could address these limitations by incorporating additional features and exploring deep learning models for more accurate predictions. Practical implications of the study suggest that e-commerce businesses can improve conversion rates by optimizing product-related pages and focusing on key user behaviors that are predictive of purchases. Bright Institute 2024-07-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/81 10.47738/ijaim.v4i2.81 International Journal for Applied Information Management; Vol. 4 No. 2 (2024): Regular Issue: July 2024 2776-8007 10.47738/ijaim.v4i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/81/74 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/82 2025-11-21T05:43:37Z ijaim:ART

Forecasting AI Model Computational Requirements Using Random Forest and XGBoost with Entity and Domain Characteristics Ayuningtyas, Astika Wulandari, Rindi Nur AI model prediction computational power Random Forest XGBoost feature importance This research aims to predict the computational power required by artificial intelligence (AI) models, specifically measured in petaFLOP (Floating Point Operations Per Second), based on their domain and entity characteristics. The study employs Random Forest and XGBoost regression models to predict the amount of computational power needed by AI models. Both models were trained on a dataset that includes features such as the training year, domain (e.g., Language, Vision), and entity characteristics. The results demonstrate that the Random Forest model outperforms XGBoost in terms of prediction accuracy, as indicated by higher R-squared values and lower error metrics. Feature importance analysis revealed that the year of training and domain were the most significant predictors of computational power, with the Language domain emerging as the most influential in both models. The findings highlight the potential for machine learning models to forecast AI computational requirements, which can aid organizations in optimizing computational resources for AI projects. However, the study faces limitations due to data sparsity, particularly in the target variable, and the relatively simple nature of the models employed. Future work should explore incorporating additional features, such as hardware specifications, and leveraging deep learning models to better capture the complexity of AI computational demands. This study lays the groundwork for further research into more precise predictions of AI model resource consumption, helping organizations plan their AI initiatives more effectively. Bright Institute 2024-07-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/82 10.47738/ijaim.v4i2.82 International Journal for Applied Information Management; Vol. 4 No. 2 (2024): Regular Issue: July 2024 2776-8007 10.47738/ijaim.v4i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/82/75 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/83 2025-11-21T05:43:37Z ijaim:ART

Predicting AI Service Focus in Companies Using Machine Learning: A Data Mining Approach with Random Forest and Support Vector Machine Sangsawang, Thosporn Tang, Lin Pasawano, Tiamyod AI service focus machine learning Random Forest Support Vector Regressor feature importance This study investigates the prediction of AI service focus in companies using machine learning models. The primary objective is to predict the percentage of AI service focus based on company characteristics such as project size, hourly rate, number of employees, and geographical location. Two machine learning models, Random Forest Regressor and Support Vector Regressor (SVR), were trained and evaluated to determine their effectiveness in predicting AI adoption. The dataset consists of 3099 companies, with key features cleaned and preprocessed, including the transformation of categorical variables into numerical ones using one-hot encoding and imputation techniques applied to handle missing values. The Random Forest model demonstrated better performance, with an R² value of 0.12, indicating a modest ability to explain the variance in AI service focus. In contrast, the SVR model had a negative R² value of -0.03, suggesting that it struggled to capture the underlying relationships in the data. The analysis identified project size and hourly rate as the most significant predictors of AI service focus, with larger projects and higher hourly rates correlating with a greater emphasis on AI services. Despite the relatively low performance of both models, this research provides valuable insights into the factors that influence AI adoption. The findings emphasize the importance of project-related characteristics in determining a company's AI service focus. However, the study is limited by missing data and the absence of additional features that could further improve prediction accuracy. Future research could benefit from incorporating more business-specific features and advanced modeling techniques to enhance the predictive power and generalizability of the model. Bright Institute 2024-07-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/83 10.47738/ijaim.v4i2.83 International Journal for Applied Information Management; Vol. 4 No. 2 (2024): Regular Issue: July 2024 2776-8007 10.47738/ijaim.v4i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/83/76 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/85 2025-11-21T03:51:42Z ijaim:ART

Unveiling Hidden Customer Segments in E-Commerce Using DBSCAN Clustering on Demographic and Behavioral Insights Aglasia, Adimas Agus, Isnandar DBSCAN Customer Segmentation E-Commerce Clustering Personalized Marketing Customer segmentation is a crucial process in e-commerce that allows businesses to tailor their marketing strategies to specific customer groups. This research applies the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to segment customers based on their demographic and behavioral data. The dataset used includes variables such as age, annual income, total spending, and campaign engagement, which are essential for identifying meaningful patterns within the customer base. The DBSCAN algorithm was chosen due to its ability to detect clusters of arbitrary shapes and handle noise, making it ideal for complex e-commerce datasets. The analysis identified one dominant customer segment, with a small portion of the data labeled as noise, indicating that the majority of customers exhibit similar behaviors. However, the results also highlight the challenge of parameter selection for DBSCAN, as the clustering outcome was sensitive to the chosen values of ε (epsilon) and MinPts. The segmentation revealed valuable insights, such as the fact that most customers share similar characteristics in terms of spending habits and engagement, yet a few outliers exist who do not align with these patterns. These findings provide a foundation for businesses to develop targeted marketing strategies based on customer segmentation. Despite the promising results, the study acknowledges limitations in the segmentation process, particularly with the influence of outliers and the need for further tuning of the algorithm's parameters. Future research could explore hybrid clustering models that combine DBSCAN with other techniques, as well as incorporating additional behavioral features for more refined segmentation. The insights gained from this research can guide businesses in crafting personalized marketing campaigns that cater to distinct customer segments. Bright Institute 2024-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/85 10.47738/ijaim.v4i3.85 International Journal for Applied Information Management; Vol. 4 No. 3 (2024): Regular Issue: September 2024; 128-140 2776-8007 10.47738/ijaim.v4i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/85/77 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/86 2025-11-21T03:51:42Z ijaim:ART

Leveraging Machine Learning to Analyze User Conversion in Mobile Pharmacy Apps Using Behavioral and Demographic Data Lestari, Sri Setiawan, Kiki Aula, Raisah Fajri machine learning user conversion mobile pharmacy app logistic regression random forest This study explores the use of machine learning techniques to predict user conversion in a mobile pharmacy app based on user behavior and demographic data. The analysis was conducted using two classification models: Logistic Regression and Random Forest. Key features such as time spent on the product page, adding items to the cart, and user demographics (age, gender, device type) were evaluated to determine their impact on conversion rates. Both models demonstrated strong performance, with the Logistic Regression model achieving an Area Under the Curve (AUC) of 0.88 and the Random Forest model achieving an AUC of 0.87. These results indicate that both models effectively distinguish between users who convert and those who do not, with Logistic Regression showing a slightly better overall performance. Feature importance analysis revealed that factors such as adding items to the cart and the time spent on the product page are the most significant predictors of conversion. Furthermore, demographic features like age group and device type also contributed to the model’s predictive power, although they had a smaller impact compared to user engagement features. The findings suggest that machine learning models, particularly Logistic Regression, can be utilized to predict user behavior and optimize user engagement strategies in mobile apps. The study also highlights the importance of user engagement in driving conversions and the potential for targeted marketing based on demographic data. Future work should focus on hyperparameter tuning, exploring additional algorithms, and incorporating real-time data to further enhance model accuracy and adaptability. Bright Institute 2024-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/86 10.47738/ijaim.v4i3.86 International Journal for Applied Information Management; Vol. 4 No. 3 (2024): Regular Issue: September 2024; 141-153 2776-8007 10.47738/ijaim.v4i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/86/78 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/87 2025-11-21T03:51:42Z ijaim:ART

Analysis of Factors Influencing Fraudulent Transactions in Digital Financial Systems Using Machine Learning Models Saputra, Jeffri Prayitno Bangkit Hidayat, Muhammad Taufik Nur Fraud Detection Machine Learning Random Forest Digital Financial Systems Transaction Analysis This paper explores the use of machine learning, specifically the Random Forest algorithm, to detect fraudulent transactions in digital financial systems. As digital finance grows, the risk of fraud increases, making effective detection systems crucial for maintaining trust and security. The study focuses on identifying key factors influencing fraudulent transactions, such as transaction amount and type, and evaluates the model's performance using accuracy, precision, recall, F1-score, and AUC-ROC metrics. Results show that Random Forest outperforms traditional methods, achieving high accuracy of 95%, precision of 1.00 for fraudulent transactions, and an AUC of 0.98, indicating excellent discriminatory power. By analyzing transaction data, the model identifies important patterns, offering financial institutions practical insights for enhancing fraud detection systems. The findings suggest that focusing on critical features like transaction amount and transfer type can optimize detection systems. However, limitations include the need for further exploration of additional features, such as user behavior, and the integration of more advanced techniques to address emerging fraud tactics. The study’s outcomes provide a robust framework for improving fraud detection in the evolving landscape of digital transactions. Bright Institute 2024-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/87 10.47738/ijaim.v4i3.87 International Journal for Applied Information Management; Vol. 4 No. 3 (2024): Regular Issue: September 2024; 154-166 2776-8007 10.47738/ijaim.v4i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/87/102 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/88 2025-11-21T03:51:42Z ijaim:ART

Sentiment Analysis on Job Descriptions in the Technology Sector: Measuring Positive and Negative Perceptions of Companies Using Natural Language Processing Techniques Yang, Liu Pigultong, Matee Sentiment Analysis Job Descriptions Technology Sector Natural Language Processing Employer Branding Sentiment analysis in job descriptions plays a critical role in shaping employer branding and recruitment strategies. This study investigates the sentiment of job postings in the technology sector using NLP techniques, focusing on the emotional tone of descriptions across various job types, companies, and subcategories. The analysis reveals that positive sentiment predominates in job descriptions, with a clear trend towards using optimistic language to attract candidates. The findings show that Software Development positions tend to have the most positive tone, while roles such as IT Management exhibit a more balanced sentiment. Additionally, the use of inclusive language, such as "equal opportunity" and "years of experience", is prevalent in the descriptions, highlighting the growing importance of diversity and inclusivity in recruitment. Visualization tools like word clouds and trend analysis illustrate how sentiment shifts over time, with a noticeable increase in positive sentiment from 2020 onwards. The results underscore the potential of sentiment analysis and NLP in optimizing recruitment processes, aligning job descriptions with candidate expectations, and enhancing employer branding strategies. Bright Institute 2024-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/88 10.47738/ijaim.v4i3.88 International Journal for Applied Information Management; Vol. 4 No. 3 (2024): Regular Issue: September 2024; 167-177 2776-8007 10.47738/ijaim.v4i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/88/80 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/89 2025-11-21T03:51:42Z ijaim:ART

Applying K-Means Clustering to Group Jobs Based on Location and Experience Level: Analysis of the Job Recommendation Kumar, Vinoth S, Priya K-Means Clustering Job Market Analysis Skill Demand Job Search Labor Market Trends Labor market analysis plays a crucial role in helping job seekers identify employment opportunities that align with their qualifications, location, and experience level. This study uses the K-Means clustering algorithm to group jobs based on these critical factors. By analyzing job market data, the research identifies the most sought-after skills across various industries and highlights the geographic and experience-level disparities in job availability. Key findings include the high demand for foundational skills such as customer service, sales, and production planning, as well as more specialized skills like Medical Research in certain sectors. The study provides actionable insights for job seekers and policymakers, suggesting that targeted skill development and training programs are essential for improving job match quality. However, the study also acknowledges its limitations, such as the lack of consideration for broader economic and social factors that influence labor market trends. Future research is recommended to address these gaps, using more comprehensive datasets and advanced analytical techniques. Bright Institute 2024-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/89 10.47738/ijaim.v4i3.89 International Journal for Applied Information Management; Vol. 4 No. 3 (2024): Regular Issue: September 2024; 178-189 2776-8007 10.47738/ijaim.v4i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/89/81 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/90 2025-11-21T05:41:54Z ijaim:ART

Optimization of Fraud Detection in E-Commerce: A CGAN Data Augmentation Approach to Address Class Imbalance Zulham Yasir, Amru Fraud Detection E-Commerce CGAN Data Augmentation Machine Learning The rapid growth of e-commerce has increased the risk of fraud in online transactions, resulting in significant financial losses and decreased consumer trust. One of the main challenges in fraud detection is data imbalance, where the number of legitimate transactions far exceeds fraudulent transactions. This imbalance causes machine learning models to fail in accurately identifying fraudulent transactions. This study aims to evaluate the effectiveness of Conditional Generative Adversarial Network (CGAN) in improving fraud detection performance in e-commerce through data augmentation. Two machine learning algorithms, Random Forest (RF) and XGBoost, were used to classify transactions in both the original imbalanced dataset and the dataset augmented with CGAN. The study uses key evaluation metrics, including accuracy, precision, recall, and F1-score, to measure the model's performance. The results show that data augmentation using CGAN significantly improved the performance of both models. RF on the augmented dataset achieved an accuracy of 99.96%, precision of 99.93%, recall of 99.99%, and F1-score of 99.96%. Meanwhile, XGBoost achieved an accuracy of 99.93%, precision of 99.91%, recall of 99.94%, and F1-score of 99.92%. The main contribution of this study is to demonstrate that CGAN can effectively address the challenge of data imbalance and improve the reliability of fraud detection systems in e-commerce. This approach has the potential to be applied in various sectors facing similar issues, such as anomaly detection in finance and cybersecurity. Bright Institute 2024-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/90 10.47738/ijaim.v4i4.90 International Journal for Applied Information Management; Vol. 4 No. 4 (2024): Regular Issue: December 2024; 190-201 2776-8007 10.47738/ijaim.v4i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/90/82 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/91 2025-11-21T05:41:54Z ijaim:ART

Analysis of Demographic and Consumer Behavior Factors on Satisfaction with AI Technology Usage in Digital Retail Using the Random Forest Algorithm Priyanto, Eko Saekhu, Ahmad Prasetyo, Priyo Agung Artificial Intelligence Consumer Satisfaction Digital Retail Random Forest Technology Adoption The rapid integration of artificial intelligence (AI) into digital retail has reshaped consumer interactions, enabling personalized services and operational enhancements. This study investigates the demographic and behavioral factors influencing consumer satisfaction with AI technologies in digital retail, using the Random Forest classification algorithm for predictive modeling. After comprehensive preprocessing and hyperparameter tuning through grid search cross-validation, the Random Forest model achieved an overall accuracy of 83%. While the model showed strong performance for predicting satisfied consumers yielding a precision of 0.84, recall of 0.97, and F1-score of 0.90, it performed poorly in identifying dissatisfied users, with a recall of only 0.27 and F1-score of 0.39, highlighting a class imbalance issue. Feature importance analysis revealed that experiential factors, particularly enhanced AI experience and preference for online services, significantly influenced satisfaction levels, whereas demographic variables such as age and gender had limited predictive value. These findings emphasize the need for digital retailers to focus on user-centric design and service personalization, rather than demographic segmentation alone, to enhance customer satisfaction and loyalty. Furthermore, the study contributes methodologically by demonstrating the effectiveness of Random Forest in handling complex consumer datasets and theoretically by validating TAM and Customer Satisfaction Theory in the context of AI adoption. Despite limitations related to class imbalance and sector-specific data, this research offers actionable insights for retailers, marketers, and system developers aiming to improve AI-driven service quality and consumer engagement. Future studies are encouraged to address these limitations through the inclusion of emotional and contextual variables and by expanding the analysis to other industries for broader applicability. Bright Institute 2024-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/91 10.47738/ijaim.v4i4.91 International Journal for Applied Information Management; Vol. 4 No. 4 (2024): Regular Issue: December 2024; 202-216 2776-8007 10.47738/ijaim.v4i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/91/83 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/92 2025-11-21T05:41:54Z ijaim:ART

User Profiling Based on Financial Transaction Patterns: A Clustering Approach for User Segmentation Pratama, Satrya Fajri Putri, Nadya Awali Profiling Financial Transactions Clustering Techniques K-Means Customer Segmentation User profiling based on financial transaction patterns is crucial for improving customer segmentation and personalizing financial services. This study uses clustering techniques, specifically K-means, to analyze transaction data and segment users based on transaction amounts, times, and types. Three clusters were identified, each demonstrating distinct transaction behaviors: Cluster 0, primarily focused on purchases and occurring early in the week; Cluster 1, which emphasizes transfers and higher transaction amounts, typically occurring mid-week; and Cluster 2, similar to Cluster 0 but with a preference for later-week transactions. The analysis demonstrates that transaction patterns, including amount, time, and type, provide valuable insights for targeting specific user groups with personalized marketing strategies and financial products. The study also highlights the importance of improving clustering accuracy, as indicated by the moderate Silhouette Score of 0.33, suggesting that further refinement in the clustering methodology could lead to more distinct user segments. The findings of this study emphasize the potential for clustering techniques to enhance user profiling, ultimately improving business strategies, customer satisfaction, and loyalty. Limitations of the study, including the dataset’s single-month duration, suggest that further research incorporating larger and more diverse datasets, as well as alternative clustering techniques, could offer deeper insights into user behavior and refine segmentation strategies. Bright Institute 2024-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/92 10.47738/ijaim.v4i4.92 International Journal for Applied Information Management; Vol. 4 No. 4 (2024): Regular Issue: December 2024; 217-228 2776-8007 10.47738/ijaim.v4i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/92/84 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/93 2025-11-21T05:41:54Z ijaim:ART

Assessing Sentiment in YouTube Video Content: A Title and Description Analysis Approach to Analyze User Reactions Sanyour, Rawan Abdullah, Manal El Emary, Ibrahiem M. M. Sentiment Analysis YouTube Engagement Emotional Tone Video Content Strategy User Interaction This study investigates the relationship between sentiment in YouTube video titles and descriptions and user engagement metrics, such as view count, like count, and comment count. The findings reveal that videos with positive sentiment generally attract higher levels of engagement, including more views, likes, and comments, while videos with negative sentiment typically receive lower interaction levels. The research emphasizes the importance of emotionally resonant content, suggesting that content creators should focus on producing videos with positive emotional tones to maximize audience interaction. Additionally, the study highlights the significance of well-crafted titles and descriptions as key drivers of engagement, as these textual elements influence viewers' initial expectations and emotional reactions. However, the study is limited to analyzing titles and descriptions, which may not fully capture the emotional tone of the video itself. Future research should incorporate the actual video content and explore additional engagement metrics, such as shares and watch time, for a more comprehensive understanding of viewer behavior. Despite these limitations, the study provides valuable insights that can guide content creators in tailoring their video content and metadata to foster greater viewer engagement and content success. Bright Institute 2024-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/93 10.47738/ijaim.v4i4.93 International Journal for Applied Information Management; Vol. 4 No. 4 (2024): Regular Issue: December 2024; 229-245 2776-8007 10.47738/ijaim.v4i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/93/85 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/94 2025-11-21T05:41:54Z ijaim:ART

Implementation of Machine Learning Algorithms for Detecting Bot and Fraudulent Accounts on Instagram Based on Public Profile Characteristics Maidin, Siti Sarah Xing, Zhang Lie, Ye Machine Learning Instagram Fake Account Detection Random Forest Social Media Security The rapid growth of Instagram as a social media platform has led to increased challenges related to fake accounts, including bots, spam, and scam profiles, which threaten the integrity and trustworthiness of online information. This study implements machine learning algorithms, particularly the Random Forest classifier, to detect and classify Instagram accounts into four categories: Real, Bot, Spam, and Scam, based on publicly available profile characteristics. A dataset of 15,000 Instagram profiles was collected and preprocessed, extracting features such as follower count, following count, posting frequency, and presence of profile information. The Random Forest model was trained and evaluated, achieving an accuracy of 97% with high precision and recall across all categories. Behavioral analysis revealed distinct patterns in following/follower ratios, posting activity, and mutual friends that differentiate genuine users from fake accounts. Feature importance ranking highlighted follower count as the most influential attribute for classification. The model demonstrated strong robustness through ROC and Precision-Recall curves, underscoring its effectiveness in a multiclass classification task. This approach not only enhances automated detection and moderation of malicious accounts but also contributes to maintaining a safer social media environment by mitigating misinformation and fraud. Future work could improve detection by incorporating temporal activity data, linguistic analysis, and real-time monitoring to adapt to evolving deceptive behaviors. Taken together, this study confirms the viability of machine learning methods in addressing the growing issue of fake accounts on Instagram, offering scalable and interpretable solutions for social media security. Bright Institute 2024-12-03 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/94 10.47738/ijaim.v4i4.94 International Journal for Applied Information Management; Vol. 4 No. 4 (2024): Regular Issue: December 2024; 246-258 2776-8007 10.47738/ijaim.v4i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/94/86 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/95 2025-11-21T06:27:37Z ijaim:ART

Enhancing Minority Class Prediction in Wearable Sensor-Based Activity Recognition Using SMOTE Oversampling Sarmini Widiawati, Chyntia Raras Ajeng Yunita, Ika Romadoni Wearable Sensors Activity Recognition Class Imbalance SMOTE XGBoost Wearable sensor-based activity recognition has become increasingly important in various domains, particularly healthcare and sports. However, a significant challenge in this field is the issue of class imbalance, where minority activity classes are underrepresented compared to majority classes in datasets. This imbalance leads to biased classifiers that struggle to accurately identify rare but critical activities, which is especially problematic in health monitoring scenarios. This study evaluates the effectiveness of the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance in the mHealth dataset, which contains multi-sensor data from wearable devices placed on the chest, left ankle, and right lower arm. We employ the XGBoost classifier combined with SMOTE oversampling to improve recognition performance for minority classes. Model evaluation is conducted using precision, recall, F1-score, Area Under the Precision-Recall Curve (AUC-PR), ROC curve, and calibration analysis. The results demonstrate that applying SMOTE improves minority class recall from 0.75 to 0.85 and F1-score from 0.796 to 0.865, despite a slight decrease in overall accuracy from 97% to 96.5%. The AUC-PR also increases from 0.81 to 0.88, indicating a better balance in detecting minority and majority classes. Calibration curves reveal that probability estimates still require refinement to be more reliable for decision-making. This study confirms the efficacy of SMOTE in mitigating class imbalance in wearable sensor-based activity recognition and provides valuable insights for developing more accurate and fair health monitoring systems. Bright Institute 2025-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/95 10.47738/ijaim.v5i1.95 International Journal for Applied Information Management; Vol. 5 No. 1 (2025): Regular Issue: April 2025; 1-15 2776-8007 10.47738/ijaim.v5i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/95/87 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/96 2025-11-21T06:27:37Z ijaim:ART

Predicting IMDb Ratings of One Piece Episodes Using Regression Models Based on Narrative and Popularity Features Hery Haryani, Calandra IMDb ratings One Piece Regression Model Narrative Analysis Viewer Engagement This study explores the predictive modeling of IMDb ratings for episodes of the anime One Piece using a linear regression approach grounded in narrative and popularity-based features. The dataset comprises 1,122 episodes, with features including story arcs, episode types, and the number of viewer votes. After one-hot encoding categorical variables and training the model using Ordinary Least Squares (OLS), the model achieved a high coefficient of determination (R² = 0.855), a low Mean Absolute Error (MAE = 0.216), and Root Mean Squared Error (RMSE = 0.329). These results indicate a strong predictive performance based on limited but interpretable features. The findings reveal that narrative structure especially arc classification and viewer engagement contribute significantly to the perceived quality of episodes. While vote counts show limited correlation with ratings, combining them with narrative elements yields reliable predictions. This research offers a novel contribution to anime-based media analytics, emphasizing that minimal feature sets can provide robust predictive insight. The study also opens opportunities for enhancing content strategies and viewer understanding in serialized storytelling. Bright Institute 2025-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/96 10.47738/ijaim.v5i1.96 International Journal for Applied Information Management; Vol. 5 No. 1 (2025): Regular Issue: April 2025; 16-29 2776-8007 10.47738/ijaim.v5i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/96/88 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/97 2025-11-21T06:27:37Z ijaim:ART

Predicting the Popularity Level of Roblox Games Using Gameplay and Metadata Features with Machine Learning Models Yi, Ding Jun, Luo Govindaraju, S Roblox Game Popularity Machine Learning Gradient Boosting Predictive Modeling The online gaming platform Roblox has become a significant player in the gaming industry, providing a space for user-generated content. Predicting the popularity of Roblox games can help developers design better games and optimize user engagement. This study explores the use of machine learning models to predict the popularity of games on Roblox using gameplay features and metadata. A dataset of 9,734 games was collected, including variables such as likes, visits, game age, and active players. Three machine learning models, Decision Tree, Random Forest, and Gradient Boosting were employed to predict the number of favorites, which serves as a proxy for game popularity. Among the models tested, Gradient Boosting outperformed the others, achieving the highest R-squared score (0.85) and the lowest Root Mean Squared Error (11,470). Key features such as likes, game age, and visits were identified as the most influential in predicting game popularity. Based on these findings, this study recommends that developers focus on features that increase player engagement, such as regular updates and optimizing game exposure. Additionally, incorporating additional data sources, such as user reviews, and exploring explainability methods like SHAP can further improve model accuracy and transparency. This research contributes valuable insights into how machine learning can support decision-making in the development and optimization of Roblox games. Bright Institute 2025-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/97 10.47738/ijaim.v5i1.97 International Journal for Applied Information Management; Vol. 5 No. 1 (2025): Regular Issue: April 2025; 30-42 2776-8007 10.47738/ijaim.v5i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/97/89 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/98 2025-11-21T06:27:37Z ijaim:ART

K-Means Clustering for Segmenting AI Survey Respondents: Analysis of Information Sources and Impact Perceptions Evelyn Suryodiningrat, Satrio Pradono Tarigan, Masmur K-Means Clustering AI Perception Information Sources Student Segmentation Higher Education This study employs K-Means clustering to analyze survey data from 91 university students, aiming to segment respondents based on their information-seeking behaviors (Question 2) and impact perceptions (Question 3) of artificial intelligence (AI). Two distinct clusters emerged: “Optimistic Problem Solvers,” who favor formal channels such as scholarly websites, peer-reviewed papers, and guided discussions, and express strong confidence in AI’s problem-solving capabilities with low concern for job displacement or dehumanization; and “Critical Watchers,” who rely more on informal, rapidly updated media (e.g., social platforms, general web searches) and exhibit heightened apprehension regarding AI’s socio-economic and ethical risks. Demographically, the former group skews toward sophomores with consistent GPAs and quantitatively oriented majors, while the latter displays broader disciplinary representation, balanced gender composition, and greater academic variability. These findings validate a dual-dimensional segmentation framework that integrates source behavior with perceptual orientation, highlighting the inadequacy of one-size-fits-all AI education. The study recommends differentiated instructional strategies, deep-dive, research-oriented modules for problem-solvers and trust-building, narrative-driven outreach for watchers, and outlines future research directions including larger, multi-institutional samples, longitudinal tracking, and mixed-methods approaches to refine and validate these profiles. Bright Institute 2025-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/98 10.47738/ijaim.v5i1.98 International Journal for Applied Information Management; Vol. 5 No. 1 (2025): Regular Issue: April 2025; 58-72 2776-8007 10.47738/ijaim.v5i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/98/91 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/99 2025-11-21T06:27:37Z ijaim:ART

Anime Segmentation Based on User Preferences: Applying Clustering to Identify Groups of Anime with Similar Genres, Themes, and Popularity Tarigan, Riswan E Wijaya, Yoana Sonia Anime Segmentation User Preferences Clustering K-means Personalization The anime industry has experienced significant growth, with an increasing focus on user preferences for content discovery and engagement. This study applies clustering techniques, specifically K-means, to segment anime based on user preferences, genres, themes, and popularity. By analyzing a comprehensive dataset containing attributes such as user ratings, popularity, genres, and themes, the research identifies distinct groups of anime that align with varying viewer tastes. The clustering results reveal that anime can be categorized into several groups, including highly popular but critically less-acclaimed titles, well-regarded but moderately popular anime, and niche, critically acclaimed series that appeal to smaller but dedicated audiences. This segmentation allows streaming platforms to offer more personalized recommendations, enhancing user experience and engagement by matching viewers with content that best fits their preferences. Although clustering techniques provide valuable insights into anime content, the study acknowledges certain limitations, such as overlap between clusters, indicating that some anime may not fit perfectly into a single category. This highlights the need for further improvements in segmentation accuracy. The study suggests exploring hybrid clustering methods, combining K-means with other techniques, and integrating demographic data, such as age, gender, and geographic location, to refine recommendations. Overall, the application of clustering algorithms to better understand user preferences in anime offers a promising approach to developing more effective and personalized recommendation systems. This can ultimately improve user satisfaction and engagement in the rapidly growing and competitive anime streaming market. Bright Institute 2025-04-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/99 10.47738/ijaim.v5i1.99 International Journal for Applied Information Management; Vol. 5 No. 1 (2025): Regular Issue: April 2025; 43-57 2776-8007 10.47738/ijaim.v5i1 eng http://ijaim.net/journal/index.php/ijaim/article/view/99/90 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/100 2025-11-21T05:50:31Z ijaim:ART

Predicting Smartphone Prices Based on Key Features Using Random Forest and Gradient Boosting Algorithms in a Data Mining Framework Wahyusari, Retno Azizah, Nur Feature Importance Gradient Boosting Price Prediction Random Forest Smartphone This study aims to predict smartphone prices using machine learning models, specifically Random Forest and Gradient Boosting algorithms, based on various smartphone features such as internal memory, RAM, processor speed, battery capacity, and camera specifications. The dataset, consisting of 980 smartphones available in India, was preprocessed to handle missing values and categorical variables, ensuring it was ready for model training. The models were evaluated using Mean Squared Error (MSE) and R-squared (R²) scores, with Gradient Boosting outperforming Random Forest in terms of predictive accuracy. Key findings from the feature importance analysis revealed that internal memory, RAM, and processor speed were the most influential features in determining smartphone prices. The results indicate that machine learning models, particularly tree-based algorithms, are effective tools for predicting smartphone prices based on hardware specifications. This study has practical implications for businesses and consumers, as it provides insights into the factors influencing smartphone prices, helping businesses optimize pricing strategies and assisting consumers in making more informed purchasing decisions. Future research could explore deep learning models and incorporate additional features, such as market demand and consumer sentiment, to improve prediction accuracy. Bright Institute 2025-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/100 10.47738/ijaim.v5i2.100 International Journal for Applied Information Management; Vol. 5 No. 2 (2025): Regular Issue: July 2025; 73-85 2776-8007 10.47738/ijaim.v5i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/100/92 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/101 2025-11-21T05:50:31Z ijaim:ART

Predicting Pharmaceutical Product Discontinuation Using Decision Tree and Random Forest Algorithms Based on Product Attributes Suhartono, Susilo Nabila, Zahara This study aims to predict the discontinuation of pharmaceutical products using machine learning models, focusing on key product attributes such as manufacturer, composition, price, and packaging. A comprehensive dataset of over 250,000 pharmaceutical products from India was analyzed, with two models—Decision Tree and Random Forest—being employed for prediction. The models were evaluated based on accuracy, precision, recall, and F1-score. The Random Forest model outperformed the Decision Tree with a higher accuracy, but both models struggled with the imbalanced dataset, showing low recall for the minority class (discontinued products). Feature importance analysis identified manufacturer and composition as the most influential factors in predicting product discontinuation. These findings offer valuable insights for pharmaceutical companies in managing product portfolios and optimizing their lifecycle strategies. Despite limitations in data quality and class imbalance, this study provides a foundation for future research, suggesting the integration of additional data sources and the application of deep learning techniques to further enhance prediction accuracy. Bright Institute 2025-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/101 10.47738/ijaim.v5i2.101 International Journal for Applied Information Management; Vol. 5 No. 2 (2025): Regular Issue: July 2025; 86-97 2776-8007 10.47738/ijaim.v5i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/101/93 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/102 2025-11-21T05:50:31Z ijaim:ART

Clustering Netflix Shows Based on Features Using K-means and Hierarchical Algorithms to Identify Content Patterns Hayadi, B Herawan Priyanto, Eko Clustering Content Strategy K-Means Netflix Recommendation System This study explores clustering patterns within Netflix's movie catalog by applying K-means and hierarchical clustering algorithms. The primary objective is to identify distinct content groups based on features such as movie duration, release year, and content ratings. The dataset, which includes 5,185 Movies, was preprocessed by handling missing values, one-hot encoding categorical variables, and standardizing numerical features. Four distinct clusters were identified, with each cluster exhibiting unique characteristics. Cluster 0 primarily consists of longer, family-friendly Movies rated TV-14, while Cluster 1 contains shorter, mature Movies with a TV-MA rating. Cluster 2 represents a diverse range of TV-MA Movies with moderate durations, and Cluster 3 focuses on adult-oriented, longer Movies with an 'R' rating. These findings offer valuable insights into Netflix's content strategy, highlighting the platform's ability to cater to different audience segments based on content type and viewer preferences. The results suggest that Netflix can leverage clustering patterns to improve its recommendation system and content acquisition strategy. However, the study is limited by the absence of user-specific data and the reliance on basic metadata features. Future research could explore the integration of additional features like user ratings and apply deep learning techniques for more sophisticated clustering. Bright Institute 2025-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/102 10.47738/ijaim.v5i2.102 International Journal for Applied Information Management; Vol. 5 No. 2 (2025): Regular Issue: July 2025; 98-110 2776-8007 10.47738/ijaim.v5i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/102/94 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/103 2025-11-21T05:50:31Z ijaim:ART

Analyzing Customer Spending Based on Transactional Data Using the Random Forest Algorithm Siddique, Quba Wahid, Arif Muamar Age Customer Spending Price Quantity Random Forest This study explores customer spending behavior using transactional data from a retail dataset, employing a Random Forest Regressor to predict the total amount spent by customers. The dataset includes various customer attributes such as age, gender, and product category, alongside transactional details including quantity purchased and price per unit. Through Exploratory Data Analysis (EDA), it was found that Price and Quantity were the most significant factors influencing total spending, with other features like Age, Gender, and Product Category playing a minimal role in predicting spending behavior. The model achieved perfect accuracy, with an R-squared value of 1.000, indicating that it explained all the variance in customer spending. The findings suggest that transactional features, particularly Price and Quantity, are the key drivers of customer spending, and retailers can optimize their marketing and sales strategies by focusing on these factors. This study also highlights the importance of data preprocessing and feature engineering in enhancing model performance, though the results were limited by the lack of external and behavioral features. Future research could further explore the impact of customer loyalty, external factors, and more complex algorithms to improve predictive accuracy. Bright Institute 2025-05-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/103 10.47738/ijaim.v5i2.103 International Journal for Applied Information Management; Vol. 5 No. 2 (2025): Regular Issue: July 2025; 111-124 2776-8007 10.47738/ijaim.v5i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/103/95 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/104 2025-11-21T05:50:31Z ijaim:ART

Clustering Sleep Patterns and Health Metrics Using K-Means Algorithm to Identify Profiles of Sleep Quality and Well-being in a Diverse Population Septiadi, Abednego Prasetyo, Muhamad Awiet Wiedanto Blood Pressure Clustering K-Means Sleep quality is a critical element of overall health that has garnered significant attention in recent years, particularly regarding its severe impacts on both physical and mental well-being. A growing body of research underscores that insufficient or poor-quality sleep is associated with various adverse health outcomes, ranging from cognitive impairments to chronic diseases. Studies have demonstrated that the duration and quality of sleep are intricately linked to physical, social, and emotional health outcomes among various populations, including adults and children (Lallukka et al., 2018). The crucial role sleep plays in regulating both physiological and psychological processes makes it an indispensable component of health maintenance. Research indicates that sleep disturbances can impede cognitive development in children, with implications for their growth and emotional regulation (Purwanti et al., 2024). For instance, infants who achieve a higher quality of sleep demonstrate improved cognitive abilities, which can lead to better academic performance and emotional health throughout their lives (Purwanti et al., 2024). These findings suggest that interventions designed to enhance sleep quality during infancy could yield substantial long-term health benefits. Furthermore, comparable patterns have been observed in adults, where good sleep quality significantly influences psychological factors such as emotion regulation and overall mental health (Scott et al., 2021). The psychological ramifications of poor sleep quality extend beyond mere cognitive performance. Poor sleep has been linked to increased rates of anxiety, depression, and other mood disorders (Becerra et al., 2022). A meta-analysis revealed that improving sleep quality could ameliorate the symptoms of these mental health conditions (Scott et al., 2021). Moreover, chronic sleep deprivation has been identified as a precursor to substance use disorders, suggesting a complex interplay between sleep, addiction, and mental health (Freeman & Gottfredson, 2018). The challenges of maintaining sleep quality have been exacerbated by external stressors such as the COVID-19 pandemic, leading to increased anxiety and altered sleep patterns among various demographics, particularly students and healthcare workers (Fan et al., 2021). Physical health is equally affected by sleep quality. Quality sleep is pivotal for metabolic regulation, immune function, and recovery from injuries. Poor sleep has been associated with a range of chronic health issues, including obesity, diabetes, and cardiovascular diseases (Du et al., 2021). For instance, individuals who experience poor sleep tend to exhibit higher dietary risks and poor lifestyle choices, leading to serious health complications (Du et al., 2021). The immunological impacts of sleep deprivation further elucidate its role in health, indicating that compromised sleep can weaken the immune system and elevate susceptibility to viral infections such as COVID-19 (Pillay et al., 2020). Bright Institute 2025-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/104 10.47738/ijaim.v5i2.104 International Journal for Applied Information Management; Vol. 5 No. 2 (2025): Regular Issue: July 2025; 125-138 2776-8007 10.47738/ijaim.v5i2 eng http://ijaim.net/journal/index.php/ijaim/article/view/104/96 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/105 2025-12-30T17:04:00Z ijaim:ART

Deciphering Weather Dynamics and Climate Shifts in Seattle for Informed Risk Management Ramadani, Nevita Nanjar, Agi Rainfall Patterns Seattle Climate Change Temperature Trends Weather Risk Management Wind Speed Dynamics This research presents a comprehensive analysis of the weather characteristics in the city of Seattle over the past few years. Through a detailed understanding of the distribution of maximum and minimum temperatures, the findings indicate significant fluctuations between summer and winter seasons. The increasing temperature trend from year to year provides insights into the potential climate changes in the region. Additionally, rainfall data reveals consistent increases over time, particularly during the winter, with significant impacts on the environment and daily life. Wind speed stability throughout the year provides insights into wind dynamics, influencing the transportation and maritime sectors. Annual averages of rainfall, sunshine hours, snowfall, and foggy days provide foundational information for long-term planning and risk management in Seattle. The percentage of rainy and clear weather throughout the year gives a comprehensive overview of the seasons, facilitating daily activity planning. Through these findings, the research aims to make a significant contribution to the understanding of the general public, natural resource managers, and economic sectors regarding the potential impacts and opportunities arising from future weather changes. It is hoped that this research can serve as a solid foundation in efforts to mitigate and adapt to the continually changing weather dynamics in the city of Seattle Bright Institute 2025-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/105 10.47738/ijaim.v5i3.105 International Journal for Applied Information Management; Vol. 5 No. 3 (2025): Regular Issue: September 2025; 190-200 2776-8007 10.47738/ijaim.v5i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/105/101 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/106 2025-12-30T17:04:00Z ijaim:ART

Predicting Future Electric Vehicle (EV) Sales: A Time Series Forecasting Approach Using Historical EV Sales Data Srinivasan, Bhavana Electric Vehicle Forecasting ARIMA LSTM Time Series Accurate forecasting of Electric Vehicle (EV) sales is essential for supporting strategic decisions by policymakers, manufacturers, and investors amid the global shift toward sustainable transportation. This study compares the performance of two time series models, AutoRegressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) using historical EV sales data from 2010 to 2023. The ARIMA model, which is suited for linear trend projection, forecasts continued exponential growth, estimating sales to surpass 103 million units by 2025. In contrast, the LSTM model, known for capturing non-linear and complex patterns, projects a more moderate trend, with sales peaking at around 11.5 million units in 2022 before gradually declining. Evaluation using Mean Squared Error (MSE) shows that LSTM significantly outperforms ARIMA, achieving a lower error value (2.23 × 10¹⁴ vs. 4.44 × 10¹⁵), indicating superior predictive accuracy. These results suggest that while ARIMA may be effective for short-term forecasting in stable markets, it can lead to overestimations in more dynamic environments. LSTM, with its ability to learn complex temporal dependencies, presents a more flexible and realistic tool for long-term planning in the evolving EV sector. The study contributes methodologically by offering a comparative analysis of two popular forecasting techniques and practically by guiding stakeholders on model selection. However, it is limited by its reliance on historical data and exclusion of external variables such as energy prices or policy changes. Future work should incorporate hybrid models and multi-source data to enhance forecasting robustness in the fast-changing EV market Bright Institute 2025-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/106 10.47738/ijaim.v5i3.106 International Journal for Applied Information Management; Vol. 5 No. 3 (2025): Regular Issue: September 2025; 177-189 2776-8007 10.47738/ijaim.v5i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/106/100 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/107 2025-12-30T17:04:00Z ijaim:ART

Anomaly Detection in Corporate Balance Sheets for Financial Risk Assessment Using Isolation Forest from 2020 to 2023 Nugroho, Khabib Turino Financial risk assessment anomaly detection balance sheet analysis Isolation Forest algorithm corporate financial stability This study aims to evaluate corporate financial risk by analyzing changes in balance sheet accounts from 2020 to 2023 using anomaly detection methods. Employing the Isolation Forest algorithm with a 5% contamination rate, we identified a consistent 3,264 anomalies each year out of a total of 65,296 entries, focusing on key accounts, including Accumulated Depreciation (61 anomalies), Additional Paid-In Capital (17 anomalies), Accounts Payable (9 anomalies), and Accounts Receivable (6 anomalies). These anomalies highlight areas of potential financial risk associated with asset valuation, capital structure, and cash flow management. The steady presence of anomalies suggests underlying, possibly systemic factors influencing financial stability. Findings indicate that significant fluctuations in Accumulated Depreciation and Additional Paid-In Capital may impact the company’s asset valuation and investor perceptions, while irregularities in Accounts Payable and Accounts Receivable suggest short-term liquidity risks. Recommendations include regular monitoring of high-risk accounts, trend analysis to identify cyclical patterns, and examining correlations with macroeconomic conditions to understand root causes. Future research should explore advanced anomaly detection models and integrate real-time detection capabilities to enhance proactive financial risk management. This study demonstrates the effectiveness of anomaly detection in identifying critical financial risks, supporting improved decision-making and corporate resilience Bright Institute 2025-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/107 10.47738/ijaim.v5i3.107 International Journal for Applied Information Management; Vol. 5 No. 3 (2025): Regular Issue: September 2025; 168-176 2776-8007 10.47738/ijaim.v5i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/107/99 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/108 2025-12-30T17:04:00Z ijaim:ART

Comparative Study of Traditional and Modern Models in Time Series Forecasting for Inflation Prediction Henderi, Henderi Sofiana, Sofa Time Series Forecasting Inflation Prediction Deep Learning Models ARIMA vs. LSTM Model Performance Evaluation Time series forecasting plays a crucial role in economic analysis, particularly in anticipating inflation and policy planning. This study compares the performance of seven different time series forecasting models, namely ARIMA, SARIMA, ETS, Prophet, LSTM, XGBoost, and TCN, in predicting inflation rates. Each model was applied to four years of inflation data to test its accuracy and reliability. The evaluation was conducted using Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) to measure the performance of each model. The results indicate that deep learning models, particularly LSTM and TCN, achieved the highest accuracy with the lowest MSE and RMSE values, specifically 0.0008 and 0.0015 for LSTM, and 0.0007 and 0.0013 for TCN, indicating their capability in capturing complex temporal patterns. Traditional models such as ARIMA and SARIMA, while effective in capturing trends and seasonality, showed limitations in handling non-linear patterns and sudden changes, with MSE and RMSE values of 0.0012 and 0.0024 for ARIMA, and 0.0011 and 0.0023 for SARIMA, respectively. ETS, with the highest MSE and RMSE values of 0.0013 and 0.0025, demonstrated limitations in dealing with the complexity of inflation data. XGBoost also showed good performance with MSE and RMSE values of 0.0009 and 0.0018, combining flexibility and robustness in handling complex data. Prophet achieved an MSE of 0.0010 and RMSE of 0.0020, indicating that while it effectively captures seasonal trends, there is room for improvement in handling rapid inflation increases. This research provides in-depth insights into the strengths and weaknesses of each model, as well as recommendations for practical applications in inflation forecasting. By presenting a comprehensive comparative analysis, this study aims to assist researchers and practitioners in selecting the most suitable forecasting model for their specific needs Bright Institute 2025-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/108 10.47738/ijaim.v5i3.108 International Journal for Applied Information Management; Vol. 5 No. 3 (2025): Regular Issue: September 2025; 155-167 2776-8007 10.47738/ijaim.v5i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/108/98 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/109 2025-12-30T17:04:00Z ijaim:ART

Clustering Students Based on Academic Performance and Social Factors: An Unsupervised Learning Approach to Identify Student Patterns Rahma, Felinda Ulfah, Siti Zayyana K-Means clustering Academic Performance Social Factors Student Grouping Educational Interventions This study explores the application of K-Means clustering, an unsupervised learning method, to group students based on academic performance and social factors. The primary objective is to uncover hidden patterns among students by analyzing academic scores in mathematics, reading, and writing, as well as demographic attributes including gender, ethnicity, parental education level, and lunch type. Data preprocessing steps, such as normalization and one-hot encoding, were conducted to prepare the dataset for clustering. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, with K=3 selected for its balance between cluster quality and interpretability. The clustering results revealed three distinct groups of students: low performers, average performers, and high performers. These clusters were visualized using PCA and t-SNE, which showed clear separation and internal consistency. Interpretation of the clusters suggests that social factors may influence academic outcomes, with students from disadvantaged backgrounds more likely to fall into the lower-performing group. The study highlights the importance of data-driven approaches in understanding student diversity and designing targeted interventions. Furthermore, this research underlines the potential of clustering techniques to inform educational strategies by identifying students' needs more precisely. However, limitations include reliance on academic and basic demographic variables, and sensitivity of the K-Means algorithm to outliers and the predefined number of clusters. Future research should incorporate additional factors such as emotional well-being and learning preferences to develop more comprehensive educational models. Overall, the study demonstrates that clustering can serve as a valuable tool for enhancing the effectiveness and equity of educational programs Bright Institute 2025-09-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/109 10.47738/ijaim.v5i3.109 International Journal for Applied Information Management; Vol. 5 No. 3 (2025): Regular Issue: September 2025; 139-154 2776-8007 10.47738/ijaim.v5i3 eng http://ijaim.net/journal/index.php/ijaim/article/view/109/97 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/111 2025-12-30T17:03:49Z ijaim:ART

Exploring Thematic Travel Preferences of Global Cities through Agglomerative Hierarchical Clustering for Enhanced Travel Recommendations Ghaffar, Soeltan Abdul Setiawan, Wilbert Clarence Travel Recommendation Agglomerative Hierarchical Clustering Thematic Preferences Clustering Analysis Personalized Travel This study explores the application of Agglomerative Hierarchical Clustering (AHC) to categorize global cities based on thematic travel preferences, aiming to enhance personalized travel recommendations. The dataset used contains travel information for 560 cities worldwide, including thematic ratings across nine categories: culture, adventure, nature, beaches, nightlife, cuisine, wellness, urban, and seclusion, along with climate data and city descriptions. Feature engineering was performed to calculate an overall rating for each city by averaging its thematic scores, and to compute an average annual temperature from monthly climate data. The primary objective of this research was to use AHC to group cities into distinct clusters based on these thematic ratings. The analysis revealed six clusters, each representing different types of travel experiences. Cluster 1 consists of urban cultural hubs with high ratings for culture, cuisine, and urban experiences, while Cluster 2 features cities with a balance of cultural and culinary experiences alongside moderate natural and nightlife attractions. Cluster 3 represents remote, nature-focused cities with high ratings for seclusion and nature. Cluster 4 includes cities renowned for their beaches, nature, and cuisine, while Cluster 5 groups cities that emphasize adventure, nature, and seclusion. Cluster 6 is made up of destinations with a focus on nature, adventure, and seclusion, offering a balance between outdoor activities and tranquility. These findings offer a deeper understanding of the diversity in global city offerings and can significantly improve the effectiveness of travel recommendation systems by aligning cities with users' thematic preferences. By categorizing cities into meaningful clusters, personalized travel suggestions can be made based on users’ specific interests, such as cultural exploration, adventure, or nature. This research lays the groundwork for future studies to incorporate additional data sources and explore alternative clustering techniques for even more refined travel recommendations. The practical applications of this research can enhance real-world travel recommendation platforms, making them more tailored and relevant to individual user preferences Bright Institute 2025-11-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/111 10.47738/ijaim.v5i4.111 International Journal for Applied Information Management; Vol. 5 No. 4 (2025): Regular Issue: December 2025; 155-167 2776-8007 10.47738/ijaim.v5i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/111/103 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/112 2025-12-30T17:03:49Z ijaim:ART

Leveraging TF-IDF and Random Forest to Uncover Genre Patterns in Google Books Metadata Putri, Nadya Awalia Mukti, Bayu Priya Genre Classification Random Forest TF-IDF Machine Learning Book Recommendation Systems This paper presents a machine learning-based approach for classifying books into genres using their descriptions. We employed a Random Forest classifier combined with Term Frequency-Inverse Document Frequency (TF-IDF) to convert text descriptions into numerical features, enabling the classification of books into six genres: Fiction, Literary Criticism, Education, Social Science, Biography & Autobiography, and Unknown Genre. The model was trained and evaluated on a dataset sourced from Google Books, which was preprocessed to remove missing data and clean the text descriptions by eliminating punctuation, numbers, and stopwords. We performed 5-fold cross-validation to assess the model's performance, which resulted in an average cross-validation accuracy of 64.22%. The final model achieved an accuracy of 62.71% on the test set, with the highest recall observed in the "Fiction" genre. The results indicated that the Random Forest classifier was particularly effective in classifying well-represented genres like "Fiction" and "Unknown Genre." However, genres with fewer samples, such as "Social Science" and "Biography & Autobiography," showed poor performance, highlighting the challenges posed by class imbalance and data sparsity. A confusion matrix and classification report revealed these discrepancies, with certain genres being misclassified more often than others. This research demonstrates the feasibility of using machine learning for automated book genre classification, offering significant potential for enhancing book recommendation systems and improving user experience. Despite its promising results, the study's limitations, including data sparsity and genre imbalance, suggest that further work is needed to refine the model. Future research could explore the use of deep learning techniques and the expansion of the dataset to address these issues and improve genre classification accuracy. The potential for automated genre classification in real-world applications, such as book categorization and personalized recommendations, presents an exciting direction for the book industry. Bright Institute 2025-11-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/112 10.47738/ijaim.v5i4.112 International Journal for Applied Information Management; Vol. 5 No. 4 (2025): Regular Issue: December 2025; 168-178 2776-8007 10.47738/ijaim.v5i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/112/104 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0

oai:ojs3.ijaim.net:article/113 2025-12-30T17:03:49Z ijaim:ART

Classifying Vehicle Categories Based on Technical Specifications Using Random Forest and SMOTE for Data Augmentation Sugianto, Dwi Wahyuningsih, Tri Vehicle Classification Random Forest SMOTE Machine Learning Market Segmentation This study investigates the application of machine learning for classifying vehicles based on their technical specifications using the Random Forest algorithm. The objective was to create a robust classification model capable of categorizing vehicles into six distinct classes: Hybrid, SUV, Sedan, Sports, Truck, and Wagon. The analysis was conducted using a comprehensive dataset that included features such as engine size, horsepower, weight, and fuel efficiency, along with the target variable, vehicle class. To address the issue of class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied to balance the training data. The results showed that the model performed particularly well in classifying Sedans, achieving a perfect recall and high F1-score, while struggling with underrepresented classes like Hybrid and Wagon. Despite applying SMOTE, the model’s performance for minority classes remained suboptimal, highlighting the challenges associated with highly imbalanced datasets. The study contributes to the field of vehicle classification by demonstrating the use of Random Forest for such tasks and providing insights into the challenges posed by imbalanced class distributions. The findings underscore the importance of feature selection, especially regarding numerical attributes such as horsepower and engine size, in improving classification accuracy. However, the study also identified limitations, including potential biases in the dataset and the difficulty in improving performance for minority vehicle classes. Future research should explore alternative algorithms like XGBoost or deep learning models, and consider expanding the dataset to include more diverse vehicle types. The practical implications of this work are significant for vehicle market segmentation, offering valuable insights for manufacturers, dealerships, and analysts seeking to optimize vehicle classification and improve market targeting strategies. Bright Institute 2025-11-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://ijaim.net/journal/index.php/ijaim/article/view/113 10.47738/ijaim.v5i4.113 International Journal for Applied Information Management; Vol. 5 No. 4 (2025): Regular Issue: December 2025; 179-191 2776-8007 10.47738/ijaim.v5i4 eng http://ijaim.net/journal/index.php/ijaim/article/view/113/105 Copyright (c) 2025 International Journal for Applied Information Management https://creativecommons.org/licenses/by-sa/4.0