Perbandingan Hasil Analisis Cluster Dengan Menggunakan Metode Average Linkage Dan Metode Ward

Studi Kasus : Kemiskinan Di Provinsi Kalimantan Timur Tahun 2018

  • Imasdiani Imasdiani Laboratorium Matematika Komputasi FMIPA Universitas Mulawarman
  • Ika Purnamasari Laboratorium Statistika Ekonomi dan Bisnis FMIPA Universitas Mulawarman
  • Fidia Deny Tisna Amijaya Laboratorium Matematika Komputasi FMIPA Universitas Mulawarman

Abstract

Hierarchical cluster analysis is an analysis used to classify data based on its characteristics. The average linkage method and the Ward method are methods of hierarchical cluster analysis. Grouping data from various aspects, one of which is poverty. This study uses poverty indicator data in East Kalimantan in 2018. The average linkage method is based on the average distance size, while the Ward method is based on the size of the distance between clusters by minimizing the number of squares. The purpose of this study was to determine the best method based on the average value of the standard deviation ratio. The results of the study using the average linkage method obtained two clusters, both the average linkage method and the Ward method both obtained two clusters. Where in the average linkage method, the first cluster consists of 7 districts / cities and the second cluster consists of 3 districts / cities. Whereas in the Ward method, the first cluster consists of 6 districts / cities and the second cluster consists of 4 districts / cities. For the best method based on the average standard deviation ratio in groups (Sw) and the standard deviation between groups (Sb), it is found that the ratio in the Ward method is smaller than the average linkage method, which is 2,681 which indicates that the average linkage method is the best method.

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Published
2022-06-09
How to Cite
IMASDIANI, Imasdiani; PURNAMASARI, Ika; AMIJAYA, Fidia Deny Tisna. Perbandingan Hasil Analisis Cluster Dengan Menggunakan Metode Average Linkage Dan Metode Ward. EKSPONENSIAL, [S.l.], v. 13, n. 1, p. 9-18, june 2022. ISSN 2798-3455. Available at: <https://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/875>. Date accessed: 14 may 2024. doi: https://doi.org/10.30872/eksponensial.v13i1.875.
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Articles