Detecting Corruption Risks in Government Procurement of Goods and Services Using Red Flag Indicators Based on LPSE Open Data: A Systematic Literature Review
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This study aims to examine the detection of corruption risks in government procurement of goods and services using an open data–based red flag indicator approach through the Electronic Procurement Services (LPSE) system. The study employed a Systematic Literature Review (SLR) method by collecting and analyzing various scientific articles related to procurement fraud, public procurement corruption, e-procurement, and the use of data analytics in fraud detection. Literature sources were obtained from several scientific databases, including Google Scholar, Scopus, ScienceDirect, and SpringerLink, covering the publication period from 2015 to 2025. The results of the study showed that the most frequently used red flag indicators in detecting procurement corruption risks included a low number of tender participants, bid values close to the Self-Estimated Price (HPS), repeated vendor wins, high use of direct appointment methods, and mass disqualification of tender participants. This study also found that LPSE open data has strong potential as an early warning system for detecting potential fraud and corruption in government procurement of goods and services. In addition, the use of data analytics, machine learning, and risk-scoring models is considered capable of improving the effectiveness of procurement oversight in a more transparent and accountable manner. This research is expected to serve as a reference for the development of a data-driven procurement monitoring system to support corruption prevention efforts in the public sector.
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