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Implementasi Algoritma Centroid Linkage dan K-Medoids dalam Mengelompokkan Kabupaten/Kota di Sulawesi Selatan Berdasarkan Indikator Pendidikan

ESTIMASI: Journal of Statistics and Its Application · Vol. 5 No. 1 (2024) · pp. 61–74

DOI
10.20956/ejsa.v5i1.13605
ISSN
2721-379X, 2721-3803
Published
2024-01-29
Publisher
Hasanuddin University
Language
en

Abstract

Cluster analysis is a multivariate analysis technique that aims to cluster the observational data or variables into clusters in such a way that each cluster is homogeneous according to the factors used for clustering. This study used the Centroid linkage algorithm that was useful for forming groups based on the distance between centroids and the K-Medoids algorithm that was based on the use of the most centered object (medoid) to group districts/cities and obtained comparison results based on the education indicator data in South Sulawesi. The implementation of the Centroid Linkage Algorithm and K-Medoids on the education indicator data in South Sulawesi in 2018, showed that the grouping of districts/cities in South Sulawesi produced 2 clusters with cluster 1 of 21 districts/cities, and cluster 2 of 3. To determine the best method, it was seen from the value of the Standard Deviation ratio in the cluster 〖(S〗_W) and Standard Deviation between Clusters 〖(S〗_B) showed the same standard deviation ratio (S) in the Centroid Linkage algorithm and K-Medoids that was equal to 104,967.

Keywords

Collaboration network of the authors

40 authors · 115 co-authorship links · showing the 40 most connected

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  • Hasanuddin University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Erna Tri HerdianiHasanuddin University9
Nurtiti SunusiHasanuddin University3
RaupongAffiliation unknown2
Anisa AnisaHasanuddin University2
Saleh AfAffiliation unknown2
Iis Cendrah KasihHasanuddin University2
Andi Kresna JayaHasanuddin University2
Anisa KalondengHasanuddin University2
Raupong RaupongHasanuddin University2
Ika FitrianaHasanuddin University1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Andi Isna YunitaHasanuddin University1
Reski AmalahAffiliation unknown1
Ratmila MammiAffiliation unknown1
Aqilah Salsabila RahmanAffiliation unknown1
Nurkamalia NurkamaliaAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Mukrimin AdamAffiliation unknown1
Nurhidaya LAffiliation unknown1
Sitti SahrimanHasanuddin University1
Hendriete Tiur Marowi WaibusiHasanuddin University1
Anisa AnisaAffiliation unknown1
Victor LimanAffiliation unknown1
Sonya SonyaAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Nuralyatussa’ AdaAffiliation unknown1
Nurul HikmahAffiliation unknown1
Parida Ayu NingsiAffiliation unknown1
Muhammad ZakirHasanuddin University1
Anna IslamiyatiHasanuddin University1
Muhammad Jayzul UsrahHasanuddin University1
Ummi SariHasanuddin University1
Fajar AffanHasanuddin University1
Alimatun NajihaHasanuddin University1
Siswanto SiswantoHasanuddin University1
Taufiq AkbarHasanuddin University1

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 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Implementasi Algoritma Centroid Linkage dan K-Medoids dalam Mengelompokkan Kabupaten/Kota di Sulawesi Selatan Berdasarkan Indikator Pendidikan</dc:title>
	<dc:creator xml:lang="en">Raja, Nur Alfianingsih</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:creator xml:lang="en">Sirajang, Nasrah</dc:creator>
	<dc:subject xml:lang="en">Centroid Linkage</dc:subject>
	<dc:subject xml:lang="en">Cluster Analysis</dc:subject>
	<dc:subject xml:lang="en">K-Medoids</dc:subject>
	<dc:subject xml:lang="en">Standard Deviation</dc:subject>
	<dc:description xml:lang="en">Cluster analysis is a multivariate analysis technique that aims to cluster the observational data or variables into clusters in such a way that each cluster is homogeneous according to the factors used for clustering. This study used the Centroid linkage algorithm that was useful for forming groups based on the distance between centroids and the K-Medoids algorithm that was based on the use of the most centered object (medoid) to group districts/cities and obtained comparison results based on the education indicator data in South Sulawesi. The implementation of the Centroid Linkage Algorithm and K-Medoids on the education indicator data in South Sulawesi in 2018, showed that the grouping of districts/cities in South Sulawesi produced 2 clusters with cluster 1 of 21 districts/cities, and cluster 2 of 3. To determine the best method, it was seen from the value of the Standard Deviation ratio in the cluster 〖(S〗_W) and Standard Deviation between Clusters 〖(S〗_B) showed the same standard deviation ratio (S) in the Centroid Linkage algorithm and K-Medoids that was equal to 104,967.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2024-01-29</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/13605</dc:identifier>
	<dc:identifier>10.20956/ejsa.v5i1.13605</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 5, No. 1, Januari, 2024 : Estimasi; 61-74</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/13605/11184</dc:relation>
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