Analysis of Crime Pattern using Data Mining Techniques

The advancement in Information Technology permits high volume of data to be generated in databases of institutions, organizations, government, including Law Enforcement Agencies (LEAs). Technologies have also been developed to store and manipulate these data to enhance decision making. Crime remains a severe threat to humanity. Criminals currently, exploit highly sophisticated technologies to perform criminal activities. To effectively combat crime, LEAs must be adequately equipped with technological tools such as data mining technology to enable useful discoveries from databases. To achieve this, a Real-time Integrated Crime Information System (RICIS) was developed and mobile phones were used by informants (general public) to capture information about crimes being committed within Southern-East, Nigeria. Each crime information captured is being sent to the LEA responsible for the crime type and the information is stored in the agency database for data analysis. Thus, this study uses data mining algorithms to analyze crime trends and patterns in Southern-Eastern part of Nigeria between 2012 and 2013. The algorithms adopted were Classification and Rule Induction. The data set of 973 were collected from Eleme Police station, PortHarcourt (2012) and Nsukka Police station (2013). The analysis enables identifications of some trends of crimes and criminal activities from various LEAs databases, enhancing crime control and public safety.