Implementasi Algoritma K-Means Untuk Mengetahui Faktor Penyebab Perceraian
DOI:
https://doi.org/10.36050/ep1sxt09Keywords:
Divorce, K-Means C Clustering, CRISP-DM, Elbow MethodAbstract
This research aims to analyze the factors causing divorce in the city of Pagar Alam using the K-Means
Clustering algorithm. Divorce data from the year 2020 to 2024 was obtained from the Religious Court. Divorce
cases in the last five years show fluctuating trends influenced by several factors. Data collection methods were
conducted through observation, interviews, literature studies, and documentation. This research adopts the K
Means algorithm with the CRISP-DM method, going through the stages of Business Understanding, Data
Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The tools used are Google Colab
with Silhouette Score testing. The research results show three clusters: C0 high with 286 cases (ongoing
disputes), C1 medium with 337 cases (economic factors), and C2 low with 494 cases (loss of one party). The
optimal cluster value k = 3 was obtained from the Elbow Method, with a Silhouette Score of 0.37
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