<![CDATA[This study aims to systematically review various digital forensic investigation models used to detect transaction fraud in e-commerce systems, based on relevant scientific literature. This study was conducted to analyze the approaches, stages, and techniques applied in each forensic investigation model, while also revealing their advantages and limitations in handling transaction fraud cases. Furthermore, this study aims to compare the effectiveness of these models in supporting the process of fraud detection, analysis, and proof in e-commerce environments. This study uses a systematic literature review methodology to collect, analyze, and integrate various studies related to forensic investigation models for identifying transaction fraud in e-commerce systems. We used keywords such as "digital forensic investigation models," "e-commerce fraud detection," "cyber forensics," and "transaction fraud" to search for articles in scientific databases including Google Scholar, IEEE Xplore, Scopus, ScienceDirect, and SpringerLink. The results demonstrate various ways to build a safer and more reliable e-commerce ecosystem for all stakeholders, requiring the integration of these three elements: early prevention in the transaction flow, ML-based detection for risk tagging, and digital forensics for evidence.]]>
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