ASC Information System Audit Using the Technology Acceptance Model

Authors

  • Tri Hartanto Darmajaya University Author

Keywords:

Audit, Assessment Center Application, TAM, Multiple Linear Regression, User Quality

Abstract

The Human Resources Bureau (Bureau HR) of Polda utilizes information technology to support its daily operations, specifically through the "Assessment Center Application System". This application is designed to enhance the effectiveness of conducting career assessments for officers holding the ranks of Iptu, AKP, and Kompol. To evaluate the success and user acceptance of this system, an information system audit was conducted using the Technology Acceptance Model (TAM). The study analyzes the relationship between four key variables: Perceived Usefulness, Perceived Ease of Use, User Acceptance, and User Quality. Using Slovin's formula, a sample size of 274 respondents was selected from a population of approximately 800 police officers. The data was analyzed using Multiple Linear Regression in SPSS. The empirical results demonstrate that while Perceived Ease of Use and User Acceptance have a significant positive effect on User Quality, Perceived Usefulness does not significantly influence User Quality. Simultaneously, the independent variables significantly explain 13.5% of the variance in User Quality, with the remaining 86.5% influenced by other external factors.

References

1. Al-Kofahi, M., Hassan, H., & Mohamad, R. (2025). DeLone and McLean information systems success model: a literature review. International Journal of Business Information Systems, 48(4), 452-481.

2. Almahri, F. A. A. J., & Saleh, N. I. M. (2025). Insights into technology acceptance: A concise review of key theories and models. Innovative and Intelligent Digital Technologies; Towards an Increased Efficiency: Volume 2, 797-807.

3. Al-Mamary, Y. H., Shamsuddin, A., & Aziati, N. (2014). The relationship between system quality, information quality, and organizational performance. International Journal of Knowledge and Research in Management & E-Commerce, 4(3), 7-10.

4. Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3).

5. Biswas, T. R., Hossain, M. Z., & Comite, U. (2024). Role of management information systems in enhancing decision-making in large-scale organizations. Pacific Journal of Business Innovation and Strategy, 1(1), 5-18.

6. Calisir, F., & Calisir, F. (2004). The relation of interface usability characteristics, perceived usefulness, and perceived ease of use to end-user satisfaction with enterprise resource planning (ERP) systems. Computers in human behavior, 20(4), 505-515.

7. Dharma, D. P. B., Sandhyaduhita, P. I., Pinem, A. A., & Hidayanto, A. N. (2017). Antecedents of intention-to-use of e-audit system: a case of the Audit Board of the Republic of Indonesia. International Journal of Business Information Systems, 26(2), 185-204.

8. Dharma, I. G. N. A., Sukadarmika, G., & Pramaita, N. (2022). Application of DeLone and McLean methods to determine supporting factors for the successful implementation of electronic medical records at Bali Mandara Eye Hospital. Journal of Applied Science, Engineering, Technology, and Education, 4(2), 146-156.

9. Diana, R., Paputungan, I. V., & Luthfi, A. (2024). Integration of TAM and DeLone and McLean Models to Evaluate the Quality of NAMPAH Applications. Jurnal Teknologi Dan Sistem Informasi Bisnis, 6(4), 723-731.

10. Harijanto, N. P., & Riantono, I. E. (2024, November). Enhancing Auditing Quality Through Big Data Analytics: A Study Leveraging the Technology Acceptance Model in Computing and Processing. In 2024 6th International Conference on Cybernetics and Intelligent System (ICORIS) (pp. 1-6). IEEE.

11. Hidayah, N. A., Hasanati, N. U., Putri, R. N., Musa, K. F., Nihayah, Z., & Muin, A. (2020, October). Analysis using the technology acceptance model (TAM) and DeLone & McLean information system (D&M IS) success model of AIS mobile user acceptance. In 2020 8th International Conference on Cyber and IT Service Management (CITSM) (pp. 1-4). IEEE.

12. Kumar, R. L., & Stylianou, A. C. (2014). A process model for analyzing and managing flexibility in information systems. European Journal of Information Systems, 23(2), 151-184.

13. Kurniati, P. S., Sholihin, I., Winarta, R., & Insan, M. H. (2021). Information technology policy through the e-government programs in improving public services quality. International Journal of Computer in Law & Political Science, 1, 1-8.

14. Laprie, J. C., & Kanoun, K. (1996). Software reliability and system reliability. Handbook for Software Reliability Engineering, 27-69.

15. Myers, B. L., Kappelman, L. A., & Prybutok, V. R. (1997). A comprehensive model for assessing the quality and productivity of the information systems function: toward a theory for information systems assessment. Information Resources Management Journal (IRMJ), 10(1), 6-26.

16. Perdiansyah, C., (2025). Design Point of Sales and Inventory System at Cafe Youth Creatino. (2026). International Journal of Information Systems and Technology, 1(05), 284–295. https://oneamd.com/JOL/index.php/IJOINT/article/view/108

17. Purwantoro, F., Purwandari, B., & Shihab, M. R. (2015, October). E-audit system acceptance in the public sector: An Indonesian perspective. In 2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) (pp. 189-194). IEEE.

18. Rafli, M. F., & Nuha, H. H. (2022, December). Analysis of SAMBARA Application Users Based on the Technology Acceptance Model (TAM) Method. In 2022 IEEE International Conference on Sustainable Engineering and Creative Computing (ICSECC) (pp. 24-29). IEEE.

19. Rusilowati, U., Narimawati, U., Wijayanti, Y. R., Rahardja, U., & Al-Kamari, O. A. (2024). Optimizing human resource planning through advanced management information systems: A technological approach. Aptisi Transactions on Technopreneurship (ATT), 6(1), 72-83.

20. Saba, P., DeLone, W., Ul-Ain, N., Harfouche, A., Ben Nasr, I., Biot-Paquerot, G., & Mallek, S. (2025). The DeLone and McLean Information Systems Success Model: What is the Future Evolution for Its Foundations, Components, and Applications?. Communications of the Association for Information Systems, 57(1), 52.

21. Sarwar, M. I., Abbas, Q., Alyas, T., Alzahrani, A., Alghamdi, T., & Alsaawy, Y. (2023). Digital transformation of public sector governance with IT service management–A pilot study. IEEE access, 11, 6490-6512.

22. Scott, M., DeLone, W., & McLean, E. (2025). Measuring the success of social information systems: an assessment of past contributions and a guide for future research. European Journal of Information Systems, 34(2), 346-366.

23. Wang, Z., Wang, Y., Zeng, Y., Su, J., & Li, Z. (2025). An investigation into the acceptance of intelligent care systems: an extended technology acceptance model (TAM). Scientific Reports, 15(1), 17912.

24. Zhou, Y., Wang, Y., & Su, J. (2025). A study on factors influencing music enthusiast’s behavioral intention to use generative AI for music composition based on an expanded technology acceptance model. Scientific Reports, 15(1), 44802.

Indonesia

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Published

2026-06-11

How to Cite

ASC Information System Audit Using the Technology Acceptance Model. (2026). International Journal of Information Systems and Technology, 2(02), 79–89. https://oneamd.com/JOL/index.php/IJOINT/article/view/117