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Lesmana, Agrian Dwi
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Computer Science & IT

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Analisis Algoritma K-Means dan Davies Bouldin Index dalam Mencari Cluster Terbaik Kasus Perceraian di Kabupaten Kuningan Sopyan, Yayan; Lesmana, Agrian Dwi; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2697

Abstract

In marriage, the thing that is most avoided is a divorce. Divorce is the termination of the husband and wife relationship which is carried out legally at the time of trial. From year to year, there is an increase in the number of divorces in Indonesia, including the number of divorces in Kuningan Regency. This study analyzes divorce cases in villages in Kuningan Regency, the analysis is carried out by using data mining clustering methods using the K-Means algorithm. The clustering method is grouping data based on the same characteristics. In determining the number of clusters by using the value of the smallest Davies Bouldin Index, it is hoped that the number of clusters formed can be more optimal. The results of this study are that there are 4 clusters consisting of villages or sub-districts with different divorce rates, namely the highest divorce rate, high divorce rate, medium divorce rate, low divorce rate, and lowest divorce rate
Co-Authors Christina Juliane, Christina Yayan Sopyan