Analisis Pola Tren Transaksi Mencurigakan Pada Aplikasi Dana Sebagai Indikator Fraud Digital Tahun 2020-2024

Abstract

This study aims to analyze suspicious transaction patterns on the DANA digital wallet application as early indicators of digital fraud. Using a descriptive quantitative approach based on secondary data, the research collects and reconstructs fraud cases from various credible sources, including academic journals, national online media reports, and official publications from the DANA platform. The analysis reveals that digital fraud patterns on DANA commonly involve social engineering, phishing, OTP misuse, fake accounts, and malware. Suspicious transaction characteristics include logins from unknown devices, unjustified refund requests, and abnormal transaction frequencies or amounts. These patterns indicate trends that can serve as early fraud indicators and contribute to the development of user behavior-based detection systems. This study emphasizes the importance of consumer data protection, digital literacy, and the enhancement of security systems based on analytical methods as preventive measures against increasingly sophisticated digital crimes.