PERAN MACHINE LEARNING DAN DEEP LEARNING DALAM PENDETEKSIAN PENCUCIAN UANG – A SYSTEMATIC LITERATURE REVIEW

Abstract

This study aims to explore and uncover the complex phenomena in the financial world, particularly concerning the prevention and mitigation of money laundering, which is becoming increasingly rampant. In an era of advancing technology, the application of artificial intelligence such as machine learning and deep learning has become essential to enhance the effectiveness of anti-money laundering systems. This research employs a systematic literature review to analyze the role of AI, machine learning, and deep learning in detecting money laundering techniques. By collecting and systematically selecting 20 articles from the Scopus database, this study provides insights into the driving factors influencing the adoption and implementation of these technologies to combat money laundering. The findings highlight the importance of advanced technology in improving compliance, security, and the speed of detection, ultimately contributing to the development of more effective anti-money laundering strategies.