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All Journal JASa (Jurnal Akuntansi, Audit dan Sistem Informasi Akuntansi)
Nurailiati, Ayke
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Computer Science & IT Economics, Econometrics & Finance

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Development of an Accounting Crime Detection Artificial Intelligence Approach Sari, Nur Zeina Maya; Nurailiati, Ayke
JASa (Jurnal Akuntansi, Audit dan Sistem Informasi Akuntansi) Vol. 10 No. 1 (2026): April
Publisher : Program Studi Akuntansi Universitas Langlangbuana Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36555/jasa.v10i1.3007

Abstract

Traditional methods of fraud detection often fall short in terms of responsiveness and adaptability. As highlighted analysis vast datasets effectively, uncovering patterns that human analysts may overlook, thereby enhancing accuracy of fraud detection efforts Research at the Bandung City Inspectorate towards detection crime fraud. The population taken is as many as 45 auditors in the inspectorate Bandung city, with take sample consisting respondents from the auditor unit and unit internal control. Method Research This use questionnaire in technique collection data. method research used is test validity and test reliability method Assumptions classic which includes test normality, test multicollinearity, test heteroscedasticity and test autocorrelation. Test hypothesis on study This use analysis regression multiple. Results main finding: Independence influential to Detection Crime fraud Because factor established standards by inspectorate the city of Bandung has in accordance with achievement expected strategy. Professionalism influential to Detection Crime fraud systems because factor transparent statement by the auditor to internal parties. Independence and Professionalism effect to crime fraud systems. Novelty a factor crime fraud prevention Detection Systems Artificial Intelligence approach.
Co-Authors Maya Sari, Nur Zeina