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p-Index From 2020 - 2025
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All Journal Applied Information System and Management International Journal for Applied Information Management
Hidayat, Muhammad Taufik Nur
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Assessing the Acceptance and Trust in Student Information Systems Through a Modified TAM Perspective Hidayat, Muhammad Taufik Nur; Hariguna, Taqwa; Saputra, Dhanar Intan Surya
Applied Information System and Management (AISM) Vol 8, No 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.42324

Abstract

The rapid development of information technology has motivated universities to implement technology-based student information systems to enhance the efficiency and effectiveness of student data management. This research seeks to evaluate acceptance and trust in student information systems at universities using a modified version of the Technology Acceptance Model, incorporating perceived trust as an additional variable. The study involved a sample of 200 active university students, with data analyzed using the structural equation modeling approach. Findings from the analysis show that both perceived usefulness and perceived ease of use significantly impact students’ intention to adopt the system, which in turn influences actual system usage. Additionally, perceived trust emerged as a critical factor in reinforcing both the intention to use and the subsequent actual use of the student information system. The results indicate that the intention to use the system acts as an essential mediator in the relationships between students’ perceptions of usefulness, ease of use, trust, and their actual usage behavior. These results have significant implications for universities aiming to improve the adoption of student information systems. Enhancing user experience, building system trust, and ensuring robust security should be prioritized in the development and refinement of such systems. By focusing on these aspects, institutions can foster higher acceptance and sustained usage, leading to more effective student data management and a better overall educational experience.
Analysis of Factors Influencing Fraudulent Transactions in Digital Financial Systems Using Machine Learning Models Saputra, Jeffri Prayitno Bangkit; Hidayat, Muhammad Taufik Nur
International Journal for Applied Information Management Vol. 4 No. 3 (2024): Regular Issue: September 2024
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v4i3.87

Abstract

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.
Assessing The Acceptance and Trust in Student Information Systems Through a Modified TAM Perspective Hidayat, Muhammad Taufik Nur; Hariguna, Taqwa; Saputra, Dhanar Intan Surya
Applied Information System and Management (AISM) Vol. 8 No. 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.42324

Abstract

The rapid development of information technology has motivated universities to implement technology-based student information systems to enhance the efficiency and effectiveness of student data management. This research seeks to evaluate acceptance and trust in student information systems at universities using a modified version of the Technology Acceptance Model, incorporating perceived trust as an additional variable. The study involved a sample of 200 active university students, with data analyzed using the structural equation modeling approach. Findings from the analysis show that both perceived usefulness and perceived ease of use significantly impact students’ intention to adopt the system, which in turn influences actual system usage. Additionally, perceived trust emerged as a critical factor in reinforcing both the intention to use and the subsequent actual use of the student information system. The results indicate that the intention to use the system acts as an essential mediator in the relationships between students’ perceptions of usefulness, ease of use, trust, and their actual usage behavior. These results have significant implications for universities aiming to improve the adoption of student information systems. Enhancing user experience, building system trust, and ensuring robust security should be prioritized in the development and refinement of such systems. By focusing on these aspects, institutions can foster higher acceptance and sustained usage, leading to more effective student data management and a better overall educational experience.
Co-Authors Bangkit, Jeffri Prayitno Dhanar Intan Surya Saputra Taqwa Hariguna