DEVELOPMENT OF CRIME AND FRAUD PREDICTION USING DATA MINING APPROACHES

Crime remains to continue to be a serious threat to all groups and peoples throughout the world together with the complexity in technology and procedures that are being manipulated to allow extremely complex criminal acts. Data mining is now an essential tool for examining, reducing, and avoiding crime and is manipulated by both government and private institutions across the globe which is the method of revealing hidden information from Big Data. The data mining methods themselves are temporarily presented to the reader and this information includes the social network analysis, neural networks, naive Bayes rule, support vector machines, decision trees, association rule mining, clustering, entity extraction, and amongst others. The main objective of this article is to offer a concise analysis of the data mining applications in crime. Finally, the article evaluates applications of data mining in crime, including a considerable quantity of the study to date, displayed in chronological order with a summary table of numerous crucial information mining applications in the crime area as a directory of reference.