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All Journal JURNAL ECONOMINA Fundamental and Applied Management Journal
Rahmat Basuki
Universitas Muhammadiyah Palembang
Economics, Econometrics & Finance Social Sciences

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The Role of Data Mining, Machine Learning, Artificial Intelligence, and Digital Forensic in Indonesian Public-Sector Fraud Detection Betri; M. Amin Dwi Putra; Fenty Astrina; Lis Djuniar; M. Faris Afif; Rendra Bakti; Mizan; Dewi Puspasari; Rahmat Basuki
Fundamental and Applied Management Journal Vol. 4 No. 2 (2026): June
Publisher : Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/famj.v4i2.994

Abstract

The Role of Data Mining, Machine Learning, Artificial Intelligence, and Digital Forensic in Indonesian Public-Sector Fraud Detection in the Indonesian public-sector audit environment. The study aims to evaluate whether advanced analytical technologies improve auditors’ effectiveness in detecting fraudulent financial reporting and whether Digital Forensic strengthens or weakens the relationships between these technologies and fraud detection performance. This study employed a causal associative quantitative approach using primary data collected through questionnaires distributed to auditors at the Financial and Development Supervisory Agency (BPKP) representative offices across Sumatra, Indonesia. The population consisted of 290 auditors, and the sample was selected using a simple random sampling technique based on the Slovin formula. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The analysis included outer model evaluation, inner model assessment, hypothesis testing, and moderation analysis. The results indicate that Data Mining has a significant positive effect on Financial Statement Fraud Detection. In contrast, Machine Learning and Artificial Intelligence do not significantly influence fraud detection effectiveness. Furthermore, Digital Forensic does not strengthen the relationships between Data Mining, Machine Learning, Artificial Intelligence, and fraud detection. Instead, the moderating effects of Digital Forensic tend to weaken these relationships within the current audit environment. The structural model demonstrates satisfactory explanatory and predictive capability in explaining variations in fraud detection performance.
Kesadaran Anti-Fraud dan Pengendalian Internal terhadap Pencegahan Fraud dalam Pengelolaan Dana Sekolah Fina Dwi Prajanti; Kurnia Krisna Hari; Nina Sabrina; Rahmat Basuki
JURNAL ECONOMINA Vol. 3 No. 5 (2024): JURNAL ECONOMINA, Mei 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/economina.v3i5.1324

Abstract

This research aims to determine the effect of anti-fraud awareness and internal control on preventing fraud in senior high schools in the city of Palembang. This type of research is associative research, the data used is primary and secondary data. Data collection methods include interviews and questionnaires. The data analysis technique uses the For Special Science (SPSS) program. The research results show that anti-fraud awareness and internal control together have an effect on preventing fraud. Anti-fraud awareness influences fraud prevention and internal control influences partial fraud prevention.
Co-Authors Dewi Puspasari Djuniar, Lis Fenty Astrina Fina Dwi Prajanti Kurnia Krisna Hari M. Amin Dwi Putra M. Faris Afif Mizan Nina Sabrina RENDRA BAKTI Sirajuddin, Betri