Cyber Romance Scam Victimization Analysis using Routine Activity Theory Versus Apriori Algorithm

The publication aims to analyze cyber romance scam victimization in Malaysia by comparing Routine Activity Theory (RAT) with Apriori algorithm approaches, using real police reports as the evidentiary basis. The researchers sought to identify key factors that may influence susceptibility to cyber romance scams and to test how well RAT and data-mining techniques capture these factors. The study draws on police data from the Commercial Crime Investigation Department and a targeted survey of victims to explore relationships among demographic variables, computer skills, cyber-fraud awareness, and victimization. Methodologically, the authors conducted a pilot test followed by a quantitative survey. They collected 280 completed surveys from cyber romance scam victims in Selangor, Malaysia, with a final usable sample of 280 after excluding incomplete responses. The instrument comprised sections on demographics, cyber-fraud awareness, and computer-related skills, and used dichotomous and Likert-scale items. Reliability was evaluated with Cronbach’s alpha (reported as 0.83–0.92 across instruments). They analyzed relationships using Pearson correlation, reporting a correlation coefficient of 0.626 between the level of cyber-fraud awareness and the tendency to become a victim. The authors also compare their findings with results derived from RAT and the Apriori algorithm to identify patterns related to victimization among victims aged 25–45 and among those with various education and skill levels. This synopsis is limited to the claims explicitly reported in the source; it does not extend to unreported methods, populations beyond the sample, or any unsupported conclusions. The article notes rising cybercrime activity in the region and emphasizes the need for improved understanding of risk factors to inform preventive measures.