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HIERARCHICAL CLUSTER ANALYSIS OF DISTRICTS/CITIES IN NORTH SUMATRA PROVINCE BASED ON HUMAN DEVELOPMENT INDEX INDICATORS USING PSEUDO-F

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 3 (2023) · pp. 1429–1438

DOI
10.30598/barekengvol17iss3pp1429-1438
ISSN
2615-3017, 1978-7227
Published
2023-09-30
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Human development is needed to create prosperity and assist development in a country. In realising this, it is necessary to first look at the quality of human resources in the country, so that its use is more targeted. The measure used as a standard for the success of human development in a country is the Human Development Index (HDI). HDI figure are calculated from the aggregation of three dimensions, namely longevity and healthy living, knowledge, and decent standard of living. The longevity and healthy living dimension is represented by the Life Expectancy. Average Years of Schooling (AYS) and Expected Years of Schooling (EYS) are indicators representing the knowledge dimension. Meanwhile, the decent standard of living dimension is represented by the Expenditure per Capita indicator. The purpose of this study is to explain the characteristics of each cluster obtained from Hierarchical Cluster Analysis of districts/cities in North Sumatra Province based on HDI indicators in 2022 using Pseudo-F. The methods used are Hierarchical Cluster Analysis and Calinski-Harabasz Pseudo-F Statistic. The main concept of this method is to determine the optimum number of groups. This research uses secondary data obtained from BPS. The sample size in this study are 33 districts/cities and the number of variables are 4 variables. The results of the analysis of this study are the formation of 4 clusters with the best method is Ward. Cluster 1 consists of four members, namely Medan City, Pematang Siantar City, Binjai City, and Padang Sidempuan City, where this cluster has a very high HDI level. Meanwhile, Cluster 4 is a cluster that has a very low HDI level with four cluster members, namely Nias District, South Nias District, North Nias District, and West Nias District. Thus, it can be seen that there is a gap between regions in North Sumatra Province.

Collaboration network of the authors

36 authors · 78 co-authorship links

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Co-authorOrganisationJoint articles
Evy SulistianingsihAffiliation unknown9
Ray TamtamaAffiliation unknown8
Wirda AndaniAffiliation unknown4
Siti AprizkiyandariAffiliation unknown4
Dadan KusnandarAffiliation unknown2
Hani Dwi RetnaniAffiliation unknown2
Inggriani Millennia TaralyAffiliation unknown2
Widad ImtiyazAffiliation unknown2
Dinda TiaraAffiliation unknown2
Fritzgerald Muhammad ArsyiAffiliation unknown2
Muhammad FauzanAffiliation unknown2
Nabila Izza HarnantaAffiliation unknown2
Nurhanifa NurhanifaAffiliation unknown2
Sania PujiantiAffiliation unknown2
Geby MarolaAffiliation unknown1
Rita ApriliyantiAffiliation unknown1
Tiffany ArdhithaAffiliation unknown1
Indah OktavianiAffiliation unknown1
Maria Welita DwinandaAffiliation unknown1
Lisa LestariAffiliation unknown1
Aditya Nugraha PratamaAffiliation unknown1
Naomi Nessyana DebatarajaAffiliation unknown1
Nurfitri Imro'ahAffiliation unknown1
Herina MarlisaAffiliation unknown1
Rifkah Alfiyyah SaryAffiliation unknown1
Ainun ZakiahAffiliation unknown1
Noerul HaninAffiliation unknown1
David Jordy DhandioAffiliation unknown1
Hairil Al-HamAffiliation unknown1
Preatin PreatinAffiliation unknown1
Louis Putra JayaAffiliation unknown1
Hendri KurniawanAffiliation unknown1
Yuyun Eka PratiwiAffiliation 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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">HIERARCHICAL CLUSTER ANALYSIS OF DISTRICTS/CITIES IN NORTH SUMATRA PROVINCE BASED ON HUMAN DEVELOPMENT INDEX INDICATORS USING PSEUDO-F</dc:title>
	<dc:creator>Satyahadewi, Neva</dc:creator>
	<dc:creator>Sinaga, Steven Jansen</dc:creator>
	<dc:creator>Perdana, Hendra</dc:creator>
	<dc:description xml:lang="en-US">Human development is needed to create prosperity and assist development in a country. In realising this, it is necessary to first look at the quality of human resources in the country, so that its use is more targeted. The measure used as a standard for the success of human development in a country is the Human Development Index (HDI). HDI figure are calculated from the aggregation of three dimensions, namely longevity and healthy living, knowledge, and decent standard of living. The longevity and healthy living dimension is represented by the Life Expectancy. Average Years of Schooling (AYS) and Expected Years of Schooling (EYS) are indicators representing the knowledge dimension. Meanwhile, the decent standard of living dimension is represented by the Expenditure per Capita indicator. The purpose of this study is to explain the characteristics of each cluster obtained from Hierarchical Cluster Analysis of districts/cities in North Sumatra Province based on HDI indicators in 2022 using Pseudo-F. The methods used are Hierarchical Cluster Analysis and Calinski-Harabasz Pseudo-F Statistic. The main concept of this method is to determine the optimum number of groups. This research uses secondary data obtained from BPS. The sample size in this study are 33 districts/cities and the number of variables are 4 variables. The results of the analysis of this study are the formation of 4 clusters with the best method is Ward. Cluster 1 consists of four members, namely Medan City, Pematang Siantar City, Binjai City, and Padang Sidempuan City, where this cluster has a very high HDI level. Meanwhile, Cluster 4 is a cluster that has a very low HDI level with four cluster members, namely Nias District, South Nias District, North Nias District, and West Nias District. Thus, it can be seen that there is a gap between regions in North Sumatra Province.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-09-30</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/8268</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss3pp1429-1438</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications; 1429-1438</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss3year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8268/6557</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Neva Satyahadewi, Steven Jansen Sinaga, Hendra Perdana</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>