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Implementation of Factor Analysis and BiClustering in Classifying Multidimensional Under-Five Poverty in East Nusa Tenggara

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 16 No. 3 (2022) · pp. 301–312

DOI
10.22146/ijccs.70433
ISSN
2460-7258, 1978-1520
Published
2022-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Under-five poverty is a condition where the needs of toodlers are not met, resulting in undernourished children and unable to reach their full potential in the social sphere. East Nusa Tenggara is a province that still faces the biggest nutritional problems in Indonesia in 2019. This study aims to explain the variables that form toodlers multidimensional poverty in East Nusa Tenggara (ENT), form the Multidimensional Under-Five Poverty Index (MUPI), and compare the results of index formed with the results of bicluster. Data source used in this study is SUSENAS KOR 2019. The analytical method used is a factor and bicluster analysis. The results shows that 11 multidimensional poverty indicators form three dimensions, namely the Adequate Food and Beverage Facility Factor, Health Protection Factor, and Housing and Nutrition Factor, which is used to form the index. Based on regional grouping, there are five areas with low MUPI scores, fourteen areas with medium MUPI scores, and three areas with high MUPI scores. However, biclustering results show that there are two areas with low poverty category, thirteen regions with moderate poverty category, and seven regions with high poverty category. The result of the comparison of MUPI grouping with the biclustering method obtained different results based on the composition of the resulting area.

Keywords

Collaboration network of the authors

4 authors · 6 co-authorship links · 3 across different organisations

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  • Politeknik Statistika STIS
  • Badan Pusat Statistik
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  • Same organisation
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Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Implementation of Factor Analysis and BiClustering  in Classifying Multidimensional Under-Five Poverty  in East Nusa Tenggara</dc:title>
	<dc:creator>Wisdawati, Rahmadathul</dc:creator>
	<dc:creator>Nooraeni, Rani</dc:creator>
	<dc:creator>Laksono, Bagaskoro Cahyo</dc:creator>
	<dc:creator>Fatah, Bintang Izzatul</dc:creator>
	<dc:subject xml:lang="en-US">Statistics;Machine learning</dc:subject>
	<dc:subject xml:lang="en-US">Under-five poverty; Factor Analysis; BiClustering</dc:subject>
	<dc:description xml:lang="en-US">Under-five poverty is a condition where the needs of toodlers are not met, resulting in undernourished children and unable to reach their full potential in the social sphere. East Nusa Tenggara is a province that still faces the biggest nutritional problems in Indonesia in 2019. This study aims to explain the variables that form toodlers multidimensional poverty in East Nusa Tenggara (ENT), form the Multidimensional Under-Five Poverty Index (MUPI), and compare the results of index formed with the results of bicluster. Data source used in this study is SUSENAS KOR 2019. The analytical method used is a factor and bicluster analysis. The results shows that 11 multidimensional poverty indicators form three dimensions, namely the Adequate Food and Beverage Facility Factor, Health Protection Factor, and Housing and Nutrition Factor, which is used to form the index. Based on regional grouping, there are five areas with low MUPI scores, fourteen areas with medium MUPI scores, and three areas with high MUPI scores. However, biclustering results show that there are two areas with low poverty category, thirteen regions with moderate poverty category, and seven regions with high poverty category. The result of the comparison of MUPI grouping with the biclustering method obtained different results based on the composition of the resulting area.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
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	<dc:date>2022-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/70433</dc:identifier>
	<dc:identifier>10.22146/ijccs.70433</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 16, No 3 (2022): July; 301-312</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/70433/34379</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
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