CRIME DATA IDENTIFICATION BASED ON EVENTS LOCATIONS IN WEST JAVA USING K-MEANS ALGORITHM

Abstract

Abstract—The problem of crime is a social problem that always demands serious attention from time to time. Moreover, according to general assumptions and some observations and research results of various parties, there is a trend of increasing development of certain forms and types of crime, both in quality and quantity. This crime does not look at place, gender, age or class. Therefore, all forms of crime must be tackled immediately because they can cause victims to suffer physical and psychological disorders. In this study, it will be explained how to collect data on the number of victims of crime that occurred in West Java based on the location of the incident which will later be processed into a data mining application program with Python language using the K-Means Clustering method. The data is calculated based on the number of cases reported by the community in each region in West Java that occurred in 2021. The K-Means Clustering method provides accuracy in grouping data and separating it by cluster categories by about 95%. In addition to calculating and grouping data based on clusters, this research is expected to help accelerate the collection of data on crime cases in West Java so that it can be handled as soon as possible by the government. As well as reducing crimes that occur in West Java with firm action based on the large data on crime in each region.