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HIERARCHICAL CLUSTER ANALYSIS ON PEOPLE'S WELFARE IN SOUTHEAST SULAWESI PROVINCE

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · hlm. 1163–1172

DOI
10.30598/barekengvol17iss2pp1163-1172
ISSN
2615-3017, 1978-7227
Terbit
2023-06-11
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Problems with people's welfare typically result from the government's development efforts in a region not being done properly or not being done equally. Consider grouping and defining the traits of each region's degree of welfare as a potential answer to ensure that development policies and strategies are well-targeted. This study aims to classify 17 regency/cities in Southeast Sulawesi province based on several indicators of people's welfare. The method used is hierarchical cluster analysis with several approaches, including Single Linkage, Complete Linkage, Average Linkage, and Ward's. The data used in this study is secondary data obtained from the publication of the Central Agency of Statistics (CAS) of Southeast Sulawesi Province. Based on the results of the evaluation the best method used is Ward's method which produces three clusters. The first cluster consists of 9 regencies, namely Buton, North Buton, South Buton, Central Buton, Muna, West Muna, Wakatobi, Konawe Islands, and East Kolaka, the majority of which come from the archipelago. Some of the problems that occur in these areas are the relatively high poverty rate and the low average length of schooling and life expectancy. The same thing happened to the second cluster which consisted of 6 regencies, namely Konawe, South Konawe, North Konawe, Bombana, Kolaka, and North Kolaka with problems of poverty, the average length of schooling, and relatively low sources of proper drinking water when compared to other clusters. The third cluster consists of 2 urban areas, namely Kendari City and Baubau City, the problems that occur are the relatively high unemployment rate and population density. The government ought to offer more initiatives to handle issues with poverty, education, and health in regions in clusters 1 and 2. While in cluster 3, the government ought to offer more initiatives to combat jobless issues and prepare for rising population densities.

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  • Universitas San Pedro
  • STIE Enam Enam Kendari
  • Universitas Gadjah Mada
  • Universitas Dian Nuswantoro
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  • Organisasi sama
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Rekan penulisOrganisasiArtikel bersama
Lidia Paskalia NipuUniversitas San Pedro1
Jus PrasetyaUniversitas Gadjah Mada1
Moch. Anjas ApriharthaUniversitas Dian Nuswantoro1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">HIERARCHICAL CLUSTER ANALYSIS ON PEOPLE'S WELFARE IN SOUTHEAST SULAWESI PROVINCE</dc:title>
	<dc:creator>Musa, Marsuddin</dc:creator>
	<dc:creator>Fallo, Sefri Imanuel</dc:creator>
	<dc:description xml:lang="en-US">Problems with people's welfare typically result from the government's development efforts in a region not being done properly or not being done equally. Consider grouping and defining the traits of each region's degree of welfare as a potential answer to ensure that development policies and strategies are well-targeted. This study aims to classify 17 regency/cities in Southeast Sulawesi province based on several indicators of people's welfare. The method used is hierarchical cluster analysis with several approaches, including Single Linkage, Complete Linkage, Average Linkage, and Ward's. The data used in this study is secondary data obtained from the publication of the Central Agency of Statistics (CAS) of Southeast Sulawesi Province. Based on the results of the evaluation the best method used is Ward's method which produces three clusters. The first cluster consists of 9 regencies, namely Buton, North Buton, South Buton, Central Buton, Muna, West Muna, Wakatobi, Konawe Islands, and East Kolaka, the majority of which come from the archipelago. Some of the problems that occur in these areas are the relatively high poverty rate and the low average length of schooling and life expectancy. The same thing happened to the second cluster which consisted of 6 regencies, namely Konawe, South Konawe, North Konawe, Bombana, Kolaka, and North Kolaka with problems of poverty, the average length of schooling, and relatively low sources of proper drinking water when compared to other clusters. The third cluster consists of 2 urban areas, namely Kendari City and Baubau City, the problems that occur are the relatively high unemployment rate and population density. The government ought to offer more initiatives to handle issues with poverty, education, and health in regions in clusters 1 and 2. While in cluster 3, the government ought to offer more initiatives to combat jobless issues and prepare for rising population densities.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8479</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp1163-1172</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 1163-1172</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8479/5978</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Marsuddin Musa, Sefri Imanuel Fallo</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>