SciRepID - Pengelompokan Data Kriminal untuk Menentukan Pola Rawan Tindak Kriminal Menggunakan Algoritma K-Means: (Studi Kasus: Polsek Hamparan Perak)

📅 20 September 2024
DOI: 10.62383/polygon.v2i5.238

Pengelompokan Data Kriminal untuk Menentukan Pola Rawan Tindak Kriminal Menggunakan Algoritma K-Means: (Studi Kasus: Polsek Hamparan Perak)

Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Asosiasi Riset Ilmu Matematika dan Sains Indonesia (ARIMSI)

📄 Abstract

Crime is a problem experienced by humans from time to time, crime often occurs because of several factors, one of which is due to the lack of security of the address so that many criminal acts occur. Hamparan Perak Police is trying to increase its commitment to safeguard and protect the community through efforts that are organized consistently and continuously. The rise of criminal acts that occur, such as motorcycle theft, persecution, and the rise of robbery in the middle of the road makes residents feel unsafe and always feel threatened at certain addresses. Therefore, to determine the vulnerable pattern of crimes committed, it is necessary to determine the group to determine the vulnerable area or not using the clustering method, which aims to be able to assist the police in conducting socialization and actions for public security by combining objects in a group with each other and different from objects in other groups. From the tests carried out using the clustering method with the K-Means algorithm, it can be seen that the group of criminal data that has the highest group and most often appears when processed is the criminal act of theft, the pattern of criminal acts in quiet areas, has been monitored and planned in klambir village.

🔖 Keywords

#Data Mining; Clustering; Crime

ℹ️ Informasi Publikasi

Tanggal Publikasi
20 September 2024
Volume / Nomor / Tahun
Volume 2, Nomor 5, Tahun 2024

📝 HOW TO CITE

Dicky Ananda Azhari; Yani Maulita; Suci Ramadani, "Pengelompokan Data Kriminal untuk Menentukan Pola Rawan Tindak Kriminal Menggunakan Algoritma K-Means: (Studi Kasus: Polsek Hamparan Perak)," Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam, vol. 2, no. 5, Sep. 2024.

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