Application of K-Means Clustering in Mapping of Central Java Crime Area

Abstract

<p>Crimes occur in many places and cause complex problems that have widespread impacts on all levels of society. Crime is related to several factors including crime index, the ratio of the number of police to the population, population density and poverty rates. In this study trying to develop an information system that is able to display and map crime-prone areas in Central Java. Based on these factors, it is used to classify regions in Central Java, namely the category of safe, quite vulnerable, vulnerable and very vulnerable. <em>K</em>-Means clustering method, is very suitable to be used in predicting and grouping which areas are included in the 4 categories. The formulation of the problem is to find out areas prone to crime in Central Java. Based on the results, there are 11 regions with safe categories, 4 areas with quite vulnerable categories, 13 regions with vulnerable categories and 6 regions with very vulnerable categories.</p><p><strong>Keywords</strong><strong> : </strong><em>K</em>-Means clustering, mapping, Central Java, criminality, crime area.</p>

Metode k-means clustering untuk mengukur tingkat kedisiplinan pegawai (studi kasus di pemerintah kabupaten padang pariaman)

“…K-Means Clustering adalah teknik pengelompokan data non-hirarki yang memisahkan data ke dalam cluster, mengelompokkan data dengan fitur yang sama, bersama-sama dan mengelompokkan data dengan karakteristik yang berbeda ke dalam kelompok yang berbeda [10] [11]. K-Means clustering merupakan algoritma unsupervised learning yang membagi data berdasarkan cluster centroid, diikuti dengan menghitung jarak antara data dan centroid yang sesuai dan menetapkan data ke centroid tertentu berdasarkan nilai jarak minimum, serta memperbarui centroid dengan menemukan nilai jarak rata-rata data yang ditetapkan dari centroid [12].…”

Application of Data Mining with the K-Means Clustering Method and Davies Bouldin Index for Grouping IMDB Movies

“…Related research that has been done by other researchers, namely the researchers Vlandari, et al, Alfianti, and Handoko, et al The research conducted by Vulandari is condcting clustering of criminal acts in the province of Central Java using the k-means clustering algorithm [7]. The data used is from 2014 to 2016, where the data obtained consists of 4 clusters.…”

Performance analysis in text clustering using k-means and k-medoids algorithms for Malay crime documents

“…Most of the research on the performance of k-means algorithms for clustering English documents makes use of publicly available data. On the other hand, several studies in the fields of crime, medicine, and finance make use of structured data [26], [31], [32].…”

“…However, not all of the studies in Table 1 employ these metrics to assess their performance. Only one study used SI [26], while the other two used DBI [32], [38].…”