Akuntansi Forensik di Era Digital: Sintesis Sistematis atas Integrasi Big Data, AI, dan Kerangka Analitik dalam Deteksi Kecurangan (2016–2025)

Penulis

  • Winda Wulandari Universitas Pancasila
  • Retna Sari Universitas Pancasila
  • Heksawan Rahmadi Universitas Pancasila
  • Wieldy Menanda Universitas Pancasila
  • Dwi Prastowo Universitas Pancasila

DOI:

https://doi.org/10.54259/akua.v5i1.5838

Kata Kunci:

Forensic Accounting, Digitalization, Governance, Fraud Prevention

Abstrak

Penelitian ini bertujuan memberikan sintesis komprehensif atas perkembangan riset akuntansi forensik di era digital periode 2016-2025 melalui pendekatan Systematic Literature Review (SLR) dengan panduan protokol PRISMA. Sebanyak 26 artikel terindeks Scopus dianalisis menggunakan kerangka Theory Context Methodology (TCM) untuk mengidentifikasi fondasi teoretis, pola metodologis, dan variasi kontekstual. Hasil kajian menunjukkan bahwa Fraud Triangle Theory masih dominan, namun mulai diintegrasikan dengan kerangka Technology Organization Environment (TOE) dan Resource-Based View (RBV) untuk menjelaskan adopsi teknologi dan kapabilitas organisasi dalam audit forensik digital. Penelitian ini mengusulkan model Forensic Accounting 4R (Regulasi Risiko Respons Reinforcement) yang menekankan sinergi antara teknologi, etika profesional, dan tata kelola. Secara teoretis, studi ini berkontribusi dalam mengintegrasikan dimensi perilaku, teknologi, dan etika ke dalam satu kerangka konseptual terpadu, sedangkan secara praktis memberikan arahan bagi peningkatan tata kelola digital dan pencegahan kecurangan di negara berkembang.

Unduhan

Data unduhan belum tersedia.

Referensi

Rezaee, Z., & Wang, J. (2019). Reinforcing forensic accounting education: Integration of big data analytics and cybersecurity. Journal of Accounting Education, 47, 1–12.

Akinbowale, O. E., Klingelhöfer, H. E., & Erasmus, L. J. (2023). Forensic accounting and big data analytics: The emerging role of artificial intelligence in fraud detection. Journal of Financial Crime, 30(1), 35–52.

Ozili, P. K. (2023). Digitalisation, ethics and accountability in forensic accounting. Journal of Financial Regulation and Compliance, 31(2), 178–192.

Alkhalaileh, M. A., Nassar, M., & Alshira’h, A. (2024). Digital transformation and forensic accounting effectiveness in Jordan. Journal of Accounting and Management Information Systems, 23(1), 45–61.

Quang, N. T., & Kien, P. V. (2025). Artificial intelligence in forensic accounting: Evidence from emerging markets.Asian Journal of Accounting Research, 10(1), 22–40.

Kaur, H., Singh, G., & Kaur, R. (2022). Integration of TOE framework in fraud prevention: A forensic accounting perspective. International Journal of Accounting Information Systems, 46, 100529.

Mandal, S., & S. Kumar. (2023). Justice theory and fraud investigation: Exploring fairness perceptions in audit environments. Journal of Business Ethics, 188(4), 965–980.

Al-Raggad, M., & Al-Raggad, A. (2024). Fraud risk assessment models: A forensic perspective. Managerial Auditing Journal, 39(2), 141–160.

Huy, N., & Phuc, T. (2024). Dynamic capabilities and forensic audit performance in Vietnam. Journal of Asian Finance, Economics and Business, 11(3), 55–68.

Panic, N., et al. (2013). Evaluation of the endorsement of the PRISMA statement by systematic reviews and meta-analyses published in surgical journals: A systematic review. PLoS ONE, 8(12), e83138.

Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019). How to do a systematic review: A best-practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology, 70, 747–770.

Moher, D., et al. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097.

Paul, J., Lim, W. M., O’Cass, A., Hao, A. W., & Bresciani, S. (2021). Scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR). International Journal of Consumer Studies, 45(6), O1–O16.

Hariningsih, E., Wahyudi, S., & Nugraha, A. (2024). Enhancing validity in forensic accounting SLR: A methodological reflection. Journal of Accounting Research and Practice, 15(2), 110–124.

Wahyudi, S. (2024). Watase Uake System for thematic extraction in digital accounting research. Indonesian Journal of Accounting Technology, 5(1), 12–25.

Afriyie, S., Appiah, K., & Boateng, R. (2022). The role of fraud triangle theory in the digital age: An extended conceptual model. Journal of Financial Crime, 29(5), 153–170.

Verhoef, G., & Samkin, G. (2022). The digital transformation of accounting: Past, present, and future trends.Accounting History Review, 32(1), 1–25.

Pham, H., & Vu, T. (2024). Emerging trends in forensic audit digitalization: A global bibliometric review (2016–2024). Journal of Forensic and Investigative Accounting, 16(3), 145–170.

Cressey, D. R. (1953). Other people’s money: A study of the social psychology of embezzlement. Glencoe, IL: The Free Press.

Botes, V., & Saadeh, A. (2018). Forensic accounting education: Insights from the Fraud Triangle perspective.Meditari Accountancy Research, 26(2), 241–263.

Alzoubi, E. (2023). Predictive analytics and anomaly detection in forensic accounting systems. Journal of Emerging Technologies in Accounting, 20(1), 25–44.

Akinbowale, O. E., et al. (2023b). AI-driven audit frameworks for fraud detection in financial institutions. Journal of Financial Crime, 30(2), 75–98.

Clavería, O., & Carrasco, A. (2022). Ethical and governance implications of machine learning in auditing. Journal of Business Research, 151, 15–29.

Gangwani, S. (2020). Corporate governance and forensic accounting: An Indian perspective. Journal of Accounting and Management Studies, 9(4), 88–102.

Imjai, K., Chong, K. M., & Wong, L. (2024). Risk-based auditing and organizational capability in detecting fraud.Journal of Asian Business and Accounting, 17(1), 75–93.

Alharasis, H., Hussein, A., & Hasan, M. (2023). Quantitative models for forensic audit performance: A systematic review approach. International Journal of Auditing, 27(2), 212–231.

Hurd, R., McKay, S., & Ozili, P. (2022). Methodological innovations in forensic accounting: Combining data science and behavioral theories. Accounting Forum, 46(4), 387–403.

Alzoubi, E., & Imjai, K. (2024). Geographical disparities in forensic accounting research output: A bibliometric mapping. Journal of Accounting and Public Policy, 43(3), 102–120.

Alkhalaileh, M. A., et al. (2024). Digital governance in forensic auditing: Evidence from developing countries.Journal of Emerging Markets Review, 46(2), 90–108.

Huy, N. T., & Phuc, T. D. (2025). Integrative model of fraud detection: Regulation, risk, and reinforcement. Asian Journal of Accounting Research, 10(2), 210–230.

Unduhan

Diterbitkan

2026-01-15

Cara Mengutip

Winda Wulandari, Retna Sari, Heksawan Rahmadi, Wieldy Menanda, & Dwi Prastowo. (2026). Akuntansi Forensik di Era Digital: Sintesis Sistematis atas Integrasi Big Data, AI, dan Kerangka Analitik dalam Deteksi Kecurangan (2016–2025). AKUA: Jurnal Akuntansi Dan Keuangan, 5(1), 1–9. https://doi.org/10.54259/akua.v5i1.5838

Terbitan

Vol 5 No 1 (2026): Januari 2026

Bagian

Articles

Lisensi

Hak Cipta (c) 2026 Winda Wulandari, Retna Sari, Heksawan Rahmadi, Wieldy Menanda, Dwi Prastowo

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