IMPLIKATIF AUDIT SUBSTANTIF BERBASIS DIGITAL ANALITIS DALAM DETEKSI KETIDAKWAJARAN TRANSAKSI

Abstract

The rapid advancement of transaction digitalization in the business environment has increased the complexity and risk of irregular transactions, making them more difficult to detect using conventional audit procedures. This study aims to analyze the implementation of digital analytics-based substantive audit and to evaluate its effectiveness in detecting transaction irregularities. The research adopts a descriptive quantitative approach using a case study based on simulated financial transaction data (dummy data) developed based on the characteristics of real-world transactions within an educational institution context. Data analysis is conducted using a statistical approach through Z-score calculation to identify outliers as indications of anomalous transactions. The findings indicate that the application of Z-score-based digital analytics enhances auditors’ ability to detect irregular transactions in a more accurate and objective manner. Furthermore, this approach provides practical implications in improving audit quality, increasing the efficiency of substantive audit procedures, and supporting data-driven decision-making by external auditors.