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All Journal SAINSMAT SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Puja Karna, I Kadek Aryandra
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Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Education Physics

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Clustering Districts/Cities In Southeast Sulawesi Province Using Fuzzy C-Means Based On Infectious Disease Cases Puja Karna, I Kadek Aryandra; Adhi Wibawa, Gusti Ngurah; Ihwal, Muhammad
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142724592025

Abstract

This study aims to determine the clustering results and characteristics of districts or cities in Southeast Sulawesi Province based on infectious disease cases in 2022 using the Fuzzy C-Means (FCM) algorithm. The analysis used the standard deviation ratio as a cluster validity measure. The clustering process produced five clusters. Cluster 1 consists of Kendari City which is characterized by a very high number of infectious disease cases. Cluster 2 includes Buton, Konawe, Bombana, North Kolaka and Baubau City which are characterized by low case numbers. Cluster 3 consists of Kolaka and South Konawe both of which have high numbers of cases. Cluster 4 includes Wakatobi, North Buton, North Konawe, East Kolaka, Konawe Islands, West Muna, Central Buton and South Buton which are characterized by very low numbers of cases. Cluster 5 consists of Muna District which is characterized by a moderately high number of infectious disease cases. These results indicate that the FCM method performs well in identifying patterns of disease spread across the region.
Clustering Districts/Cities In Southeast Sulawesi Province Using Fuzzy C-Means Based On Infectious Disease Cases Puja Karna, I Kadek Aryandra; Adhi Wibawa, Gusti Ngurah; Ihwal, Muhammad
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142724592025

Abstract

This study aims to determine the clustering results and characteristics of districts or cities in Southeast Sulawesi Province based on infectious disease cases in 2022 using the Fuzzy C-Means (FCM) algorithm. The analysis used the standard deviation ratio as a cluster validity measure. The clustering process produced five clusters. Cluster 1 consists of Kendari City which is characterized by a very high number of infectious disease cases. Cluster 2 includes Buton, Konawe, Bombana, North Kolaka and Baubau City which are characterized by low case numbers. Cluster 3 consists of Kolaka and South Konawe both of which have high numbers of cases. Cluster 4 includes Wakatobi, North Buton, North Konawe, East Kolaka, Konawe Islands, West Muna, Central Buton and South Buton which are characterized by very low numbers of cases. Cluster 5 consists of Muna District which is characterized by a moderately high number of infectious disease cases. These results indicate that the FCM method performs well in identifying patterns of disease spread across the region.
Co-Authors Adhi Wibawa, Gusti Ngurah Ihwal, Muhammad