Analisis Clustering Kasus Bunuh Diri di Jawa Tengah dengan Menerapkan Algoritma K-Means

Widya Kurniawan; Faisal Reza Pradhana; Khusna Amalia Zen

doi:10.22236/teknoka.v9i1.17559

Authors

Widya Kurniawan Universitas Darussalam Gontor
Faisal Reza Pradhana Universitas Darussalam Gontor
Khusna Amalia Zen Universitas Darussalam Gontor

DOI:

https://doi.org/10.22236/teknoka.v9i1.17559

Keywords:

Klasterisasi, K-Means, Bunuh Diri, CRISP-DM

Abstract

Suicide is a deliberate act intended to end one’s life. In Indonesia, this phenomenon remains prevalent and is influenced by various factors, such as psychological conditions, economic pressures, social issues, and environmental factors. This study aims to identify patterns of suicide cases using Clustering techniques, with data sourced from the Semarang and Boyolali Police Departments. The three main variables analyzed are age range, suicide method, and location of the incident. The CRISP-DM approach is applied for data processing, and the K-Means algorithm is used to group relevant data based on these variables. A Silhouette score of 84% indicates a good separation between clusters. Visualization with Principal Component Analysis (PCA) is used to map the clusters more comprehensively. The most vulnerable group to commit suicide is individuals in the productive age range, who tend to use hanging as the method and do so in private homes. This study is expected further insights into the suicide phenomenon in Indonesia.

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