Enhancing Crime Prediction Using K-Means with PSO

Abstract

The effects of social media and modern approaches help offenders to achieve their crimes. This paper explores machine learning architecture to predict criminal crime cases by classifying each type of crime using K-Means which is optimized with PSO from the data the researcher got in the past mas. The clustering parameters use medium, light, and severe crime categories, each of them gets medium = 74, light = 46, and weight = 30. According to the experimental result, K-Means optimization with PSO can produce 0,12287 which uses SSE parameters while k-means performance gets results 0.885.