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Penggunaan Metode Fuzzy C-Means untuk Pengelompokan Kabupaten/Kota Berdasarkan Jumlah Tenaga Kesehatan

ESTIMASI: Journal of Statistics and Its Application · Vol. 7 No. 1 (2026) · pp. 24–38

DOI
10.20956/ejsa.v7i1.29906
ISSN
2721-379X, 2721-3803
Published
2026-05-05
Publisher
Hasanuddin University
Language
en

Abstract

Clustering is the process of partitioning data into a number of clusters, which in the cluster have similar characteristics to one another and have differences with other clusters. In this study, clustering is used to group district/cities based on the number of health workers in South Sulawesi using fuzzy c-means. To get the results of grouping, there are 11 health worker variables used. In determining the optimum number of clusters, the Pseudo F-Statistic is used. In the first test, the optimum cluster was obtained in 5 groups and the second test was in 6 groups without makassar and bone. From the clustering analysis in the first test, it was found that groups 2 and 3 only have one member. In the second test, group 1 had 4 members, groups 2 and 6 had 3 members, group 3 had 2 members, and groups 4 and 5 had 5 members.

Keywords

Collaboration network of the authors

40 authors · 116 co-authorship links · showing the 40 most connected

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  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Erna Tri HerdianiAffiliation unknown4
Nasrah SirajangAffiliation unknown3
RaupongAffiliation unknown3
Anna IslamiyatiAffiliation unknown2
Nirwan IlyasAffiliation unknown2
Iis Cendrah KasihAffiliation unknown1
Ika FitrianaAffiliation unknown1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Nur Alfianingsih RajaAffiliation unknown1
Fitri FitriAffiliation unknown1
Aqilah Salsabila RahmanAffiliation unknown1
Nurkamalia NurkamaliaAffiliation unknown1
Nurul IkhsaniAffiliation unknown1
Nurhidaya LAffiliation unknown1
SuritmanAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Hendriete Tiur Marowi WaibusiAffiliation unknown1
Anisa AnisaSultan Ageng Tirtayasa University1
Victor LimanAffiliation unknown1
Sonya SonyaAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Afifah Mutiah NurdinAffiliation unknown1
Muh. Indirwan ArfanAffiliation unknown1
Kevin Ekarinaldo PalunganAffiliation unknown1
Muhammad FadilAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
A. Elisha WulandariAffiliation unknown1
Belia Nurul FajriAffiliation unknown1
Abdullah PannuAffiliation unknown1
Alfian Akbar VallarinoAffiliation unknown1
Anugrah Nur Isnaeni RahmanAffiliation unknown1
Muh. HadriantoAffiliation unknown1
Rita Ruth Chendra ChendraAffiliation unknown1
Abdul Fathin FawwazAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Penggunaan Metode Fuzzy C-Means untuk Pengelompokan Kabupaten/Kota Berdasarkan Jumlah Tenaga Kesehatan</dc:title>
	<dc:creator xml:lang="en">Syam, Surya Cahyadi</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:creator xml:lang="en">Kalondeng, Anisa</dc:creator>
	<dc:subject xml:lang="en">Clustering</dc:subject>
	<dc:subject xml:lang="en">Fuzzy C-Means</dc:subject>
	<dc:subject xml:lang="en">Group</dc:subject>
	<dc:subject xml:lang="en">Health Workers</dc:subject>
	<dc:subject xml:lang="en">Pseudo F-Statistic</dc:subject>
	<dc:description xml:lang="en">Clustering is the process of partitioning data into a number of clusters, which in the cluster have similar characteristics to one another and have differences with other clusters. In this study, clustering is used to group district/cities based on the number of health workers in South Sulawesi using fuzzy c-means. To get the results of grouping, there are 11 health worker variables used. In determining the optimum number of clusters, the Pseudo F-Statistic is used. In the first test, the optimum cluster was obtained in 5 groups and the second test was in 6 groups without makassar and bone. From the clustering analysis in the first test, it was found that groups 2 and 3 only have one member. In the second test, group 1 had 4 members, groups 2 and 6 had 3 members, group 3 had 2 members, and groups 4 and 5 had 5 members.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2026-05-05</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/29906</dc:identifier>
	<dc:identifier>10.20956/ejsa.v7i1.29906</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 7, No. 1, Januari, 2026 : Estimasi; 24-38</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/29906/14380</dc:relation>
</oai_dc:dc>