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Grouping Districts/Cities in Kalimantan Island Based on The People's Welfare Indicators Using Fuzzy C-Means and Subtractive Fuzzy C-Means Methods

PENGELOMPOKAN KABUPATEN/KOTA DI PULAU KALIMANTAN BERDASARKAN INDIKATOR KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS

Jurnal Matematika, Statistika dan Komputasi · Vol. 18 No. 1 (2021) · pp. 141–149

DOI
10.20956/j.v18i1.14416
ISSN
2614-8811, 1858-1382
Published
2021-09-02
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Cluster analysis has the aim of grouping several objects of observation based on the data found in the information to describe the objects and their relationships. The grouping method used in this research is the Fuzzy C-Means (FCM) and Subtractive Fuzzy C-Means (SFCM) methods. The two grouping methods were applied to the people's welfare indicator data in 42 regencies/cities on the island of Kalimantan. The purpose of this study was to obtain the results of grouping districts/cities on the island of Kalimantan based on indicators of people's welfare and to obtain the results of a comparison of the FCM and SFCM methods. Based on the results of the analysis, the FCM and SFCM methods yield the same conclusions, so that in this study the FCM and SFCM methods are both good to use in classifying districts/cities on the island of Kalimantan based on people's welfare indicators and produce an optimal cluster of two clusters, namely the first cluster consisting of 10 Regencies/Cities on the island of Kalimantan, while the second cluster consists of 32 districts/cities on the island of Borneo.

Bahasa Indonesia

Analisis klaster mempunyai tujuan untuk mengelompokkan beberapa objek pengamatan berdasarkan data yang ditemukan dalam informasi untuk menggambarkan objek dan hubungannya. Metode pengelompokan yang digunakan dalam penelitian ini adalah metode Fuzzy C-Means (FCM) dan Subtractive Fuzzy C-Means (SFCM). Dua metode pengelompokan tersebut diterapkan pada data indikator kesejahteraan rakyat pada 42 Kabupaten/Kota di Pulau Kalimantan. Tujuan dari penelitian ini adalah untuk mendapatkan hasil pengelompokan Kabupaten/Kota di Pulau Kalimantan berdasarkan indikator kesejahteraan rakyat serta untuk memperoleh hasil perbandingan metode FCM dan SFCM. Berdasarkan hasil analisis, metode FCM dan SFCM menghasilkan kesimpulan yang sama sehingga pada penelitian ini metode FCM dan SFCM sama-sama baik untuk digunakan dalam mengelompokkan Kabupaten/Kota di Pulau Kalimantan berdasarkan indikator kesejahteraan rakyat dan menghasilkan klaster optimal sebanyak dua klaster yaitu klaster pertama beranggotakan 10 Kabupaten/Kota di Pulau Kalimantan sedangkan klaster kedua beranggotakan 32 Kabupaten/Kota di Pulau Kalimantan.

Keywords

Collaboration network of the authors

18 authors · 31 co-authorship links

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Co-authorOrganisationJoint articles
Putri Sri AstutiAffiliation unknown2
Hairi SeptiyanorAffiliation unknown1
Syaripuddin SyaripuddinAffiliation unknown1
Reni PratiwiAffiliation unknown1
Surya PranggaAffiliation unknown1
Sifriyani SifriyaniAffiliation unknown1
Yunda Sasha ParadillaAffiliation unknown1
Sri WahyuningsihAffiliation unknown1
Kartika RamadaniAffiliation unknown1
Fidia Deny Tisna AmijayaAffiliation unknown1
Dwi Indra YunistyaAffiliation unknown1
Suyitno SuyitnoAffiliation unknown1
Ineu SintiaAffiliation unknown1
M. FathurahmanAffiliation unknown1
Ardiman WiranataAffiliation 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/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Grouping Districts/Cities in Kalimantan Island Based on The People's Welfare Indicators Using Fuzzy C-Means and Subtractive Fuzzy C-Means Methods</dc:title>
	<dc:title xml:lang="id">PENGELOMPOKAN KABUPATEN/KOTA DI PULAU KALIMANTAN BERDASARKAN INDIKATOR KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS </dc:title>
	<dc:creator xml:lang="en">Fitri, Nur Annisa </dc:creator>
	<dc:creator xml:lang="en">Hayati, Memi Nor </dc:creator>
	<dc:creator xml:lang="en">Goejantoro, Rito </dc:creator>
	<dc:subject xml:lang="en">FCM</dc:subject>
	<dc:subject xml:lang="en">People's Welfare Indicators</dc:subject>
	<dc:subject xml:lang="en">SFCM</dc:subject>
	<dc:subject xml:lang="en">validity index</dc:subject>
	<dc:subject xml:lang="id">FCM</dc:subject>
	<dc:subject xml:lang="id">Indeks Validitas</dc:subject>
	<dc:subject xml:lang="id">Indikator Kesejahteraan Rakyat</dc:subject>
	<dc:subject xml:lang="id">SFCM</dc:subject>
	<dc:description xml:lang="en">Cluster analysis has the aim of grouping several objects of observation based on the data found in the information to describe the objects and their relationships. The grouping method used in this research is the Fuzzy C-Means (FCM) and Subtractive Fuzzy C-Means (SFCM) methods. The two grouping methods were applied to the people's welfare indicator data in 42 regencies/cities on the island of Kalimantan. The purpose of this study was to obtain the results of grouping districts/cities on the island of Kalimantan based on indicators of people's welfare and to obtain the results of a comparison of the FCM and SFCM methods. Based on the results of the analysis, the FCM and SFCM methods yield the same conclusions, so that in this study the FCM and SFCM methods are both good to use in classifying districts/cities on the island of Kalimantan based on people's welfare indicators and produce an optimal cluster of two clusters, namely the first cluster consisting of 10 Regencies/Cities on the island of Kalimantan, while the second cluster consists of 32 districts/cities on the island of Borneo.</dc:description>
	<dc:description xml:lang="id">Analisis klaster mempunyai tujuan untuk mengelompokkan beberapa objek pengamatan berdasarkan data yang ditemukan dalam informasi untuk menggambarkan objek dan hubungannya. Metode pengelompokan yang digunakan dalam penelitian ini adalah metode Fuzzy C-Means (FCM) dan Subtractive Fuzzy C-Means (SFCM). Dua metode pengelompokan tersebut diterapkan pada data indikator kesejahteraan rakyat pada 42 Kabupaten/Kota di Pulau Kalimantan. Tujuan dari penelitian ini adalah untuk mendapatkan hasil pengelompokan Kabupaten/Kota di Pulau Kalimantan berdasarkan indikator kesejahteraan rakyat serta untuk memperoleh hasil perbandingan metode FCM dan SFCM. Berdasarkan hasil analisis, metode FCM dan SFCM menghasilkan kesimpulan yang sama sehingga pada penelitian ini metode FCM dan SFCM sama-sama baik untuk digunakan dalam mengelompokkan Kabupaten/Kota di Pulau Kalimantan berdasarkan indikator kesejahteraan rakyat dan menghasilkan klaster optimal sebanyak dua klaster yaitu klaster pertama beranggotakan 10 Kabupaten/Kota di Pulau Kalimantan sedangkan klaster kedua beranggotakan 32 Kabupaten/Kota di Pulau Kalimantan.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2021-09-02</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/jmsk/article/view/14416</dc:identifier>
	<dc:identifier>10.20956/j.v18i1.14416</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 18 No. 1 (2021): September 2021; 141-149</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/14416/7313</dc:relation>
	<dc:relation>10.20956/j.v18i1.14416.g7313</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2021 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>