Implementasi Metode K-Means Clustering Dengan Davies Bouldin Index Pada Analisis Faktor Penyebab Perceraian

  • Esty Purwaningsih Universitas Bina Sarana Informatika
  • Ela Nurelasari Universitas Bina Sarana Informatika

Abstract

Basically, divorce is the release of the marital relationship between partners. In this country, the number of divorce cases has reached its peak in the last six years. Many reasons can lead to divorce, such as financial problems, leaving a partner, domestic violence, or polygamy. In this study, the K-Means clustering method, which is assisted by the Davies Bouldin index, shows an advantage in solving clustering problems. Rapid Studio software is used to process secondary data. The data were tested with the values k=3, k=5, and k=7. The results showed that the k=3 group obtained a value of -0.419, the k=5 group obtained a value of -0.423, and the k=7 group obtained a value of -0.337. Thus, it can be concluded that the K-Means clustering method using the Davies Bouldin index has a value of k=7, which is the best cluster compared to the values of k=3 and k=5. The following clusters were generated from research conducted on the K-Means method with a value of k = 7 using the Davies Bouldin Index: Cluster_0 consists of "Provinsi Jawa Barat", Cluster_1 consists of "Kota Tasikmalaya", Custer_2 consists of "Cirebon" and "Indramayu", Cluster_3 consists of "Tasikmalaya", "Kuningan" and "Subang", Cluster_4 consists of "Bogor", "Cianjur", "Sumedang"

Author Biographies

Esty Purwaningsih, Universitas Bina Sarana Informatika
Sistem Informasi
Ela Nurelasari, Universitas Bina Sarana Informatika
Sistem Informasi

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Published
2023-06-29
How to Cite
PURWANINGSIH, Esty; NURELASARI, Ela. Implementasi Metode K-Means Clustering Dengan Davies Bouldin Index Pada Analisis Faktor Penyebab Perceraian. INFORMATION MANAGEMENT FOR EDUCATORS AND PROFESSIONALS : Journal of Information Management, [S.l.], v. 7, n. 2, p. 134-143, june 2023. ISSN 2548-3331. Available at: <http://ejournal-binainsani.ac.id/index.php/IMBI/article/view/2307>. Date accessed: 06 sep. 2024. doi: https://doi.org/10.51211/imbi.v7i2.2307.