Implementasi Metode Clusterisasi K-Means Pada Pemetaan Daerah Rawan Kriminal Kota Dili Berbasis WebGIS


  • Elisabet Maria Universitas Narotama
  • Latipah Universitas Narotama



Crime, Data Mining, Clustering, K-Measn, GIS, WebGIS


This study aims to map sub-districts that are prone to criminal acts with data mining to group criminal data using k-means clustering, as well as visualize into a webgis-based criminal information system by displaying a map of the distribution of criminal data and the percentage of each sub-district. -district of the city of Dili. After carrying out a series of processes, it was found that the sub-district of dom aleixo which shows a very vulnerable status area with the type of crime of assault has a high percentage of total victims with a value of 49.6%, theft 19.6%, harassment 12%, prostitution 9.6%, murder 6.8% and finally drugs with a percentage of 2.4%.


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How to Cite

Elisabet Maria, & Latipah. (2021). Implementasi Metode Clusterisasi K-Means Pada Pemetaan Daerah Rawan Kriminal Kota Dili Berbasis WebGIS. Systemic: Information System and Informatics Journal, 7(1), 19–24.