GEOGRAPHIC INFORMATION SYSTEM OF CRIMINALITY PROBLEM CLUSTERING USING HIERARCHICAL CLUSTERING METHOD

Abstract

According to the Head of Criminal Investigation at the Ternate Police, it is possible that criminal cases from year to year are increasing in number, with this large amount of data the process of clustering areas prone to crime becomes difficult and sometimes inaccurate. The crime rate recorded by the Ternate Police in 2018 with a number of different crimes according to the type of crime. Crime is indeed a common problem that often occurs in everyday life, including the city of Ternate. Various criminal acts that occurred in Ternate City with different times and places and types of crime, people find it difficult to get information on the location of crime-prone areas and safe areas. To overcome this problem, a Geographic Information System is needed to clustering areas prone to crime. GIS is a special information system that is used to process data that contains spatial information. GIS can also be combined with the clustering method. The clustering method I use is Hierarchical Clustering. Hierarchical Clustering is a bottom-up clusteringmethod, which combines several cluster into a single cluster. The results of Hierarchical Clustering are the merging of the 2 smallest groups and then combined into a single group, while the clustering of crime-prone areas is seen from the number of crimes. The purpose of this system is to create a GIS application for clustering crime-prone areas in Ternate City, especially North Ternate, Central Ternate, and South Ternate. The result of this application is to provide information to the police and the public about areas that are prone to crime in Ternate City.