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Pengelompokan Data Kriminal untuk Menentukan Pola Rawan Tindak Kriminal Menggunakan Algoritma K-Means

2024· article· en· 0 citations· W4404619263 sur OpenAlex· 10.62383/polygon.v2i5.238

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Le tri à trois modèles

les 1 000 travaux triés →

Les trois modèles l'ont jugé hors champ.

strate : aff_core · poids de sondage : 5595.24 (l'échantillon est stratifié ; tout taux calculé sans le poids est faux)
Claude Opus 4.8OUT
genre : empirical
porte sur le Canada: non
confiance: high

K-means clustering of crime data to identify high-risk areas; applied data mining.

GPT-5.6 (high)OUT
genre : empirical
porte sur le Canada: non
confiance: high

This applies clustering to criminal data and does not study research itself.

Grok 4.5OUT
genre : empirical
porte sur le Canada: non
confiance: high

Applied K-means clustering of local crime data for police operations.

Résumé

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.

Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.

La notice

Revue
Polygon Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Thématique
Data Mining and Machine Learning Applications
Domaine
Computer Science
Établissements canadiens
Kootenay Association for Science & Technology
Organismes subventionnaires
Mots-clés
Cluster analysisCriminologySocializationPersecutionComputer securityPsychologyBusinessComputer sciencePolitical scienceSocial psychologyLawArtificial intelligencePolitics
Résumé présent dans OpenAlex
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