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CLUSTERING KABUPATEN/KOTA PROVINSI SULAWESI TENGGARA BERDASARKAN INDIKATOR KESEJAHTERAAN RAKYAT

SemanTIK: Teknik Informasi · Vol. 4 No. 2 (2018) · pp. 175–182

DOI
10.55679/semantik.v4i2.5235
ISSN
2502-8928, 2460-1446
Published
2018-12-28
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The problem of people's welfare is a problem that must be faced by developing countries such as Indonesia. Many indicators affect the level of people's welfare, such as population, education, levels and patterns of consumption, poverty, housing, and the environment. To make it easier in preparing plans or making decisions on issues of people's welfare, the government needs data and information regarding the level of people's welfare. Therefore, determining the level of people's welfare needs to be done.This study is intended to produce information on clustering districts/cities in Southeast Sulawesi Province based on indicators of people's welfare using the K-Means algorithm. The process of determining clusters consists of three processes i.e. Process of Collecting Datasets, Process of Clustering, and Process of Cluster Interpretation.The data used are data on people's welfare indicators from 12 districts/cities in Southeast Sulawesi for 2014. The data consists of seven variables, i.e. the Number of Health Facilities, Life Expectancy, the Projected Total Population, the Percentage of Non-Poor People, the Number of Administrative Regions, the Average Length of School, and Spending Per Capita. Based on the results of cluster analysis, it was found that the number of cluster members with low, medium, and high welfare indicators are 3, 6, and 3, respectively.Keywords—K-Means Algorithm, Cluster Analysis, Social WelfareDOI: 10.5281/zenodo.2528154

Keywords

Collaboration network of the authors

35 authors · 105 co-authorship links · 1 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Halu Oleo
  • King Abdulaziz University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Gunawan GunawanUniversitas Halu Oleo3
Natalis RansiUniversitas Halu Oleo2
La SurimiUniversitas Halu Oleo2
Ruslan RuslanAffiliation unknown2
Wa Ode IrmayadaniUniversitas Halu Oleo1
Jumadil NangiUniversitas Halu Oleo1
Abdullah Malik Fajar ThahaUniversitas Halu Oleo1
GunawanUniversitas Halu Oleo1
La Ode Muhammad Ilham SetiawanUniversitas Halu Oleo1
Gusti Arviana RahmanUniversitas Halu Oleo1
Auni TiftazaniUniversitas Halu Oleo1
La Ode Muhammad Hafidz Abdillah Sam MongkitoUniversitas Halu Oleo1
Budi Wijaya RaufUniversitas Halu Oleo1
Ferdinand Murni HamunduUniversitas Halu Oleo1
Herdi BudimanUniversitas Halu Oleo1
Juang JulianUniversitas Halu Oleo1
Putu Nara Kusuma PrasanjayaUniversitas Halu Oleo1
Achirul Slamet SugiartoAffiliation unknown1
La Ode SaidiAffiliation unknown1
Ferdinand Murni HamunduAffiliation unknown1
Ahmad Hoirul BasoriKing Abdulaziz University1
Makkulau MakkulauAffiliation unknown1
Adham Panggu RumandaAffiliation unknown1
Andi Muhammad Islah H. MansyurAffiliation unknown1
Nana SumarnaUniversitas Halu Oleo1
Fuji astutiAffiliation unknown1
Muhibi MuhibiAffiliation unknown1
Baharuddin BaharuddinAffiliation unknown1
Mukhsar MukhsarAffiliation unknown1
Ida UsmanAffiliation unknown1
Rahmalia SahupalaAffiliation unknown1
Edi CahyonoUniversitas Halu Oleo1
Lilis LaomeAffiliation unknown1
Norma Muhtar MuhtarAffiliation 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://ojs.uho.ac.id/index.php/semantik/oai, first harvested 29 Oct 2026, last seen 29 Oct 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">CLUSTERING  KABUPATEN/KOTA PROVINSI SULAWESI TENGGARA BERDASARKAN INDIKATOR KESEJAHTERAAN RAKYAT</dc:title>
	<dc:creator>Tenriawaru, Andi</dc:creator>
	<dc:subject xml:lang="en-US">Software Engineering</dc:subject>
	<dc:description xml:lang="en-US">The problem of people's welfare is a problem that must be faced by developing countries such as Indonesia. Many indicators affect the level of people's welfare, such as population, education, levels and patterns of consumption, poverty, housing, and the environment. To make it easier in preparing plans or making decisions on issues of people's welfare, the government needs data and information regarding the level of people's welfare. Therefore, determining the level of people's welfare needs to be done.This study is intended to produce information on clustering districts/cities in Southeast Sulawesi Province based on indicators of people's welfare using the K-Means algorithm. The process of determining clusters consists of three processes i.e. Process of Collecting Datasets, Process of Clustering, and Process of Cluster Interpretation.The data used are data on people's welfare indicators from 12 districts/cities in Southeast Sulawesi for 2014. The data consists of seven variables, i.e. the Number of Health Facilities, Life Expectancy, the Projected Total Population, the Percentage of Non-Poor People, the Number of Administrative Regions, the Average Length of School, and Spending Per Capita. Based on the results of cluster analysis, it was found that the number of cluster members with low, medium, and high welfare indicators are 3, 6, and 3, respectively.Keywords—K-Means Algorithm, Cluster Analysis, Social WelfareDOI : 10.5281/zenodo.2528154</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2018-12-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs.uho.ac.id/index.php/semantik/article/view/5235</dc:identifier>
	<dc:identifier>10.55679/semantik.v4i2.5235</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol 4, No 2 (2018): semanTIK; 175-182</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:source>10.55679/semantik.v4i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/semantik/article/view/5235/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 semanTIK</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>