DOI: https://doi.org/10.14710/j.gauss.13.2.373-382

PERBANDINGAN METODE FUZZY C-MEANS DAN GUSTAFSON-KESSEL DALAM PENENTUAN CLUSTER TINGKAT RISIKO PENULARAN TUBERCULOSIS TERHADAP PENYAKIT DI JAWA TIMUR

*Atika Nurzida  -  Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
Iut Tri Utami  -  , Indonesia
Masithoh Yessi Rochayani  -  , Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Tuberculosis (TB) is a type of disease that is easily transmitted to people with weak immune systems. The disease factors that are most susceptible to TB transmission in East Java Province are Diabetes Mellitus (DM) sufferers, malnutrition toddlers, and HIV sufferers. The aim of this study was to form clusters in districts/cities with DM sufferers, malnutrition toddlers, and HIV sufferers to minimize the risk of TB transmission. Fuzzy clustering analyzes that are often used are Fuzzy C-Means and Gustafson-Kessel. Fuzzy C-Means uses the Euclidean distance squared function to form spherical clusters, while Gustafson-Kessel uses the Mahalanobis distance squared function to form ellipsoid clusters. The optimal number of clusters is determined by the Dunn Index (DI) value. The results showed that the formation of regional clusters was optimal in the Gustafson-Kessel method with 2 clusters as indicated by a DI value of 0.974603. Cluster 1 consists of 4 regencies/cities with an average of DM sufferers, malnutrition toddlers, and HIV sufferers namely 86.448 people, 2.841 people, and 87 people. Cluster 2 consists of 34 districts/cities with an average of DM sufferers, malnutrition toddlers, and HIV sufferers namely 10.449 people, 3.364 people, and 72 people.

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Perbandingan Metode Fuzzy C-Means dan Gustafson-Kessel Clustering untuk Mengelompokkan Tingkat Risiko Penularan Tuberculosis
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Keywords: Clustering, Fuzzy C-Means, Gustafson-Kessel, Dunn Index, Tuberculosis

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