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All Journal Mandalika Mathematics and Educations Journal Eksponensial
Rito Goejantoro
Mulawarman University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Fuzzy geographically weighted clustering pada pengelompokan kabupaten/kota di Kalimantan berdasarkan indikator indeks pembangunan manusia Milda Alfitri Diani; Memi Nor Hayati; Rito Goejantoro
Mandalika Mathematics and Educations Journal Vol 7 No 4 (2025): Desember
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i4.9977

Abstract

Fuzzy Geographically Weighted Clustering (FGWC) is a method of development of fuzzy clustering by considering geographical elements in the process of regional clustering. This study aims to identify the number and characteristics of optimal clusters formed using the FGWC algorithm with the validity index of the Partition Coefficient Index (PCI). The data analyzed includes HDI indicators for all regencies/cities on the island of Kalimantan in 2024 consisting of the variables Life Expectancy, Length of Schooling, Average School Length, Expenditure per Capita, Open Unemployment Rate, and Percentage of Poor Population. Based on the results of the study, the optimal number of clusters was obtained as many as 2 clusters with a PCI of 0.516. Cluster 1 consists of 18 regencies/cities covering 9 cities and 9 regencies with higher average values of HDI indicator variables, while cluster 2 consists of 38 regencies which are all dominated by inland areas with lower average values of HDI indicator variables.
Penerapan Metode K-Harmonic Means pada Pengelompokan Kabupaten/Kota di Pulau Kalimantan Berdasarkan Indikator Perumahan dan Kesehatan Lingkungan Fany Novianti; Rito Goejantoro; Memi Nor Hayati
EKSPONENSIAL Vol. 17 No. 1 (2026): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v17i1.1586

Abstract

Cluster analysis is grouping data into subsets whose members have a high degree of similarity. One commonly used clustering technique is the K-Harmonic Means, an enhancement of the K-Means method, which assigns data to clusters by calculating the harmonic mean of distances from each point to the cluster centers. This study aims to determine the optimal grouping of Regencies/Cities in Kalimantan Island based on housing and environmental health indicators and to identify the best Dunn index value. Based on the grouping results, 5 groups were obtained with parameters (p) = 2. The optimal Dunn index value is 0.2171. Based on the description of the housing and environmental health indicators, it can be seen that there are still disparities between groups in terms of access to basic services, such as the percentage of clean drinking water source services, the percentage of lighting sources from PLN electricity, the percentage of proper sanitation services, and the percentage of home ownership status. Group 4 and group 2 are groups that need special attention because they have the lowest achievements in several important indicators
Co-Authors Fany Novianti Memi Nor Hayati Milda Alfitri Diani