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Pengelompokan Data Kriminal Pada Poldasu Menentukan Pola Daerah Rawan Tindak Kriminal Menggunakan Data Mining Algoritma K-Means Clustering

Lilis Suriani

2020Jurnal Sistem Komputer dan Informatika (JSON)28 citationsDOIOpen Access PDF

Abstract

Crime is all forms of actions and actions that are economically and psychologically harmful that violate the applicable laws in the Indonesian state and social and religious norms. Can be interpreted that, crime is anything that violates the law and violates social norms, so that the public opposes it. This study aims to facilitate and assist law enforcement authorities in anticipating criminal acts in vulnerable areas. The method used in this research is the k-means algorithm method using rapidminer 7.3 software. Where the grouping is done to determine the level of vulnerable areas. The establishment of this system is expected to assist the police in determining areas prone to crime. And from the results of the study stated groups of areas prone to criminal acts, namely MEDAN POLRESTA and LABUHAN BATU POLRES.

Topics & Concepts

Law enforcementIndonesianCluster analysisState (computer science)CriminologyLawComputer scienceSociologyBusinessPolitical scienceArtificial intelligenceAlgorithmPhilosophyLinguisticsData Mining and Machine Learning ApplicationsEdcuational Technology SystemsMultimedia Learning Systems
Pengelompokan Data Kriminal Pada Poldasu Menentukan Pola Daerah Rawan Tindak Kriminal Menggunakan Data Mining Algoritma K-Means Clustering | Litcius