A Model for Visual and Intuitive Crime Investigation Based on Associative Rule Mining Technique (VICIBARM): A Case Study of Kenya

Abstract

Crime has been part of our society ever since the concept of laws was first approved. There is an increased concern at governance level due to escalating levels of crime both internationally as well as locally in Kenya. Large amounts of raw data are recorded in the occurrence books of many police stations. This data can be intelligently analyzed and visualized to assist law enforcement agencies in understanding these crimes and taking steps to ensure they remain ahead of the criminal elements. Data mining and visual analysis can be used for advanced crime analysis. In this article, the researcher suggests the use of Associative Rule Mining to come up with a model suitable for crime analysis and prevention using Apriori algorithm to represent mutual implications among criminal occurrences. This model is aimed at providing better understanding of crime patterns and helping law enforcement plan on preventive future crime policy.