Detection of Fraud and the Independence of the Corruption Eradication Commission (KPK) in Corruption Cases Using a Forensic Data Analysis Approach
Keywords:
Forensic Data Analysis; Fraud Detection; KPK; Institutional Independence; Corruption; Systematic Literature Review.Abstract
This study investigates the detection of fraud and the institutional independence of the Corruption Eradication Commission (KPK) in handling corruption cases through a forensic data analysis approach. Using a Systematic Literature Review (SLR), it synthesizes findings from previous research on how forensic data analysis techniques such as anomaly detection, network transaction analysis, and forensic accounting enhance the identification of corrupt practices. The review reveals that data accessibility, analytical capability, and integration of digital forensic tools significantly influence the effectiveness of fraud detection. Moreover, the independence of KPK, including its legal authority, organizational autonomy, and protection from political interference, moderates the success of forensic data driven investigations. When institutional independence is strong, forensic data analysis is more accurately applied, producing clearer evidentiary patterns and more decisive legal outcomes. This study integrates insights from forensic analytics, institutional theory, and anti-corruption governance, offering implications for strengthening digital forensic capacity and safeguarding institutional autonomy in corruption eradication efforts.
References
Aidt, T. S. (2016). Corruption, institutions, and economic development. Oxford University Press.
Bierstaker, J. (2017). Auditor responsibility and fraud detection: A contemporary review. Journal of Forensic & Investigative Accounting, 9(2), 288–310.
Butt, S. (2020). Anti-corruption reform in Indonesia: An institutional perspective. Asian Journal of Comparative Law, 15(1), 45–67.
Dang, N., & Phan, T. (2023). Forensic data analytics in detecting financial irregularities: A systematic analysis. Journal of Digital Forensics, 5(3), 120–138.
Englich, B., Mussweiler, T., & Strack, F. (2006). Playing dice with criminal sentences: The influence of irrelevant anchors on experts’ judicial decision making. Personality and Social Psychology Bulletin, 32(2), 188–200.
Ghosh, A., & Wang, S. (2020). Financial reporting fraud: A review of determinants and detection techniques. Accounting Perspectives, 19(1), 67–95.
Johnston, M. (2021). Corruption control in the modern state: Strategies and challenges. Routledge.
Krishnan, R., Khan, S., & Yu, Q. (2020). Forensic analytics and corruption detection: Emerging tools in digital investigation. Journal of Forensic Accounting Research, 8(1), 55–78.
Lenz, H., & Reif, S. (2020). Judicial cognition and the impact of heuristics on legal decision making. Law & Human Behavior, 44(4), 311–325.
Murphy, P., & Free, C. (2021). The psychology of fraud: Understanding motivations and organizational dynamics. Accounting, Organizations and Society, 92(2), 1–15.
Omar, N., & Din, H. (2021). Fraud detection using forensic accounting techniques: A systematic approach. Journal of Financial Crime, 28(3), 829–845.
Rezaee, Z. (2018). Financial statement fraud: Prevention and detection (3rd ed.). Wiley.
Rezaee, Z. (2019). Digital forensics and data-driven fraud detection. Journal of Emerging Technologies in Accounting, 16(2), 99–118.
Rest, J. (1986). Moral development: Advances in research and theory. Praeger.
Rose-Ackerman, S. (2017). Corruption and government: Causes, consequences, and reform (2nd ed.). Cambridge University Press.
Schütte, S. A. (2022). Anti-corruption agencies: Political independence and performance indicators. Crime, Law and Social Change, 78(2), 147–165.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Ahmad Braja Wahyu
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
International Conference On Islamic Community Studies, Education and Science, its website, and the articles published therein are licensed under a 
