Skripsi

PEMILIHAN CLUSTER OPTIMAL UNTUK PENGELOMPOKKAN PROVINSI RAWAN KRIMINALITAS DI INDONESIA BERDASARKAN 5 METODE EVALUASI MENGGUNAKAN K-MEANS CLUSTERING

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Penilaian

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Cluster analysis is one method that is usually used to group objects into groups that are similar to each other based on their characteristics. This study aims to cluster 34 provinces in Indonesia based on the number of crime cases in 2022 using the K-Means clustering method. Provinces are grouped based on crime cases, which include 8 variables, namely murder, domestic violence, rape, kidnapping, theft, narcotics, fraud, and public order violations. Determination of the optimal number of clusters with k=2, 3, 4, and 5 clusters was done by evaluation using five methods, namely Calinski Harabasz Index, Davies Bouldin Index, Elbow, Silhouette Coefficient, and Standard Deviation ratio. The results showed that the optimal number of clusters using the Calinski Harabasz Index, elbow, and standard deviation ratio methods was 4 clusters, while the Davies Bouldin Index and Silhouette Coefficient method was 2 clusters. Selection of the best clusters from 5 evaluation methods based on the results that have the most similarity because it is concluded that the results obtained are more representative and more accurate so that the best cluster selected is 4 clusters. Clustering in cluster 1 consists of 2 provinces consisting of North Sumatra and East Java Provinces with the variables of rape and fraud cases at a high level, while the other 6 variables are at a very high level. Cluster 2 consists of 3 provinces consisting of DKI Jakarta, West Java and South Sulawesi Provinces with the variables of rape, kidnapping and fraud cases at a very high level, while the other 5 variables are at a high level. Cluster 3 consists of 6 provinces consisting of Aceh, Riau, South Sumatra, Lampung, Central Java, and North Sulawesi with all variables at a high level. The remaining provinces are in cluster 4, which consists of 23 provinces with all variables at a medium level.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507001798	T169472	T1694722025	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1694722025

Publisher

Indralaya : Prodi Pendidikan Matematika, Fakultas Keguruan dan Ilmu Pendidikan Universitas Sriwijaya., 2025

Collation

xv, 69 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

510.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Matematika
Prodi Pendidikan Matematika

Specific Detail Info

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Statement of Responsibility

TUTI

Other version/related

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