Big Data Analytics dalam Audit Internal Perusahaan Publik - Nurul Rahmadani Rizanty; Roslina Roslina; Rahmat Widia Sembiring (Jurnal Penelitian Ekonomi Manajemen dan Bisnis, 2026)
Digital transformation has significantly increased data complexity and risk exposure in public companies, demanding internal audit functions that are adaptive, innovative, and technology-oriented. This study aims to analyze the implementation of Big Data Analytics (BDA) in internal auditing and examine its impact on audit effectiveness. The research adopts a qualitative approach using a case study method, focusing on PT Telkom Indonesia (Persero) Tbk through an in-depth analysis of its 2024 corporate reports and related governance documents. The findings reveal that the adoption of BDA facilitates a transition toward data-driven auditing practices, enabling more comprehensive analysis of large datasets in real time. Furthermore, BDA enhances the detection of risks, irregularities, and potential anomalies, while also improving the accuracy and efficiency of audit procedures. The implementation of analytics-based auditing strengthens the strategic role of internal audit in supporting transparency, accountability, and effective corporate governance. Overall, these results emphasize the growing importance of big data analytics in enhancing internal audit effectiveness within the rapidly evolving digital business environment.