CLUSTERING ANALYSIS OF SUICIDE CASES IN CENTRAL JAVA BY APPLYING THE K-MEANS ALGORITHM

Zen, Khusna Amalia (2025) CLUSTERING ANALYSIS OF SUICIDE CASES IN CENTRAL JAVA BY APPLYING THE K-MEANS ALGORITHM. S1 Undergraduate thesis, Universitas Darussalam Gontor.

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Abstract

Suicide is an act aimed at intentionally ending one’s life. Suicide cases are a serious issue that remains prevalent in Indonesia, particularly in Central Java, which has experienced an increasing trend in recent years. This study aims to analyze the patterns of suicide cases using the K-Means Clustering algorithm based on attributes such as age range, suicide method, and incident location. The CRISP-DM approach is applied in the data processing stages of this research. The study utilizes data from 103 cases obtained from the Semarang and Boyolali District Police Departments. The analysis process produces three risk categories: High Risk, Medium Risk, and Low Risk, which are visualized using Principal Component Analysis (PCA). The model evaluation uses the Elbow method and the Silhouette Score, indicating adequate clustering results. The silhouette score obtained from this study is 38%, which suggests that the quality of separation between clusters is quite good. Based on the clustering results, the high-risk group is dominated by elderly individuals hanging in open areas. This study provides critical insights into the distribution patterns of suicide cases in the research area. This information can be utilized to formulate more effective and targeted prevention strategies to reduce suicide rates in the future.

Item Type:	Thesis ( S1 Undergraduate )
Additional Information:	SKRIPSI: Khusna Amalia Zen NIM: 422021618037
Uncontrolled Keywords:	Suicide, Clustering, K-Means, CRISP-DM
Subjects:	Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 000 - Ilmu komputer, informasi dan pekerjaan umum 23rd Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 000 - Ilmu komputer, informasi dan pekerjaan umum Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 004 - Pemrosesan data dan ilmu komputer 23rd Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 004 - Pemrosesan data dan ilmu komputer Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 005 - Pemrograman komputer, program dan data 23rd Dewey Decimal Classification > 000 - Komputer, Informasi dan Referensi Umum > 000 - Ilmu komputer, informasi dan pekerjaan umum > 005 - Pemrograman komputer, program dan data
Divisions:	Fakultas Sains dan Teknologi UNIDA Gontor > Teknik Informatika
Depositing User:	2021 Khusna Amalia Zen
Date Deposited:	15 Feb 2025 03:04
Last Modified:	15 Feb 2025 03:04
URI:	http://repo.unida.gontor.ac.id/id/eprint/5428

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