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Identification of Factors that Influence Stunting Cases in South Sulawesi using Geographically Weighted Regression Modeling

Jurnal Matematika, Statistika dan Komputasi · Vol. 19 No. 1 (2022) · hlm. 100–108

DOI
10.20956/j.v19i1.21617
ISSN
2614-8811, 1858-1382
Terbit
2022-09-07
Penerbit
Department of Mathematics, Hasanuddin University
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

In Indonesia, nearly seven million children under five are stunted and throughout the world, Indonesia is the country with the fifth-highest stunting prevalence. South Sulawesi ranks fourth with a high stunting potential in Indonesia. Stunting is caused by multi-dimensional factors and not only due to malnutrition experienced by pregnant women and children under five. In more detail, several factors that cause stunting are the effects of poor care, the lack of household/family access to nutritious food, and the lack of access to clean water and sanitation. In addition to maternal characteristics and parenting, the problem of stunting is also influenced by environmental factors and geographical conditions (population density, climatic conditions, and inadequate sanitation) so the spatial analysis is important to do in overcoming this problem. In spatial data, often observations at a location (space) depend on observations at other locations that are nearby (neighboring). By using Geographically Weighted Regression (GWR) obtained variables that affect the prevalence of stunting in South Sulawesi Province, including the percentage of babies receiving vitamin A intake, the percentage of babies receiving exclusive breastfeeding, the percentage of babies receiving health care, the percentage of malnourished children under five, the percentage short toddlers, the percentage of infants receiving DPT-HB-Hib, Measles and BCG immunizations. for the GWR model is 81.32% and based on variables that are significant to the prevalence of stunting in South Sulawesi Province, three clusters are formed.

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Budi AyuningsihPadjadjaran University1
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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Identification of Factors that Influence Stunting Cases in South Sulawesi using Geographically Weighted Regression Modeling</dc:title>
	<dc:creator xml:lang="en">Siswanto, Siswanto</dc:creator>
	<dc:creator xml:lang="en">Mirna, Mirna</dc:creator>
	<dc:creator xml:lang="en">Yusran, Muhammad </dc:creator>
	<dc:creator xml:lang="en">Syam, Ummul Auliyah </dc:creator>
	<dc:creator xml:lang="en">Miolo, Alya Safira Irtiqa </dc:creator>
	<dc:subject xml:lang="en">children</dc:subject>
	<dc:subject xml:lang="en">geographically weighted regression</dc:subject>
	<dc:subject xml:lang="en">stunting</dc:subject>
	<dc:description xml:lang="en">In Indonesia, nearly seven million children under five are stunted and throughout the world, Indonesia is the country with the fifth-highest stunting prevalence. South Sulawesi ranks fourth with a high stunting potential in Indonesia. Stunting is caused by multi-dimensional factors and not only due to malnutrition experienced by pregnant women and children under five. In more detail, several factors that cause stunting are the effects of poor care, the lack of household/family access to nutritious food, and the lack of access to clean water and sanitation. In addition to maternal characteristics and parenting, the problem of stunting is also influenced by environmental factors and geographical conditions (population density, climatic conditions, and inadequate sanitation) so the spatial analysis is important to do in overcoming this problem. In spatial data, often observations at a location (space) depend on observations at other locations that are nearby (neighboring). By using Geographically Weighted Regression (GWR) obtained variables that affect the prevalence of stunting in South Sulawesi Province, including the percentage of babies receiving vitamin A intake, the percentage of babies receiving exclusive breastfeeding, the percentage of babies receiving health care, the percentage of malnourished children under five, the percentage short toddlers, the percentage of infants receiving DPT-HB-Hib, Measles and BCG immunizations.  for the GWR model is 81.32% and based on variables that are significant to the prevalence of stunting in South Sulawesi Province, three clusters are formed.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2022-09-07</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/21617</dc:identifier>
	<dc:identifier>10.20956/j.v19i1.21617</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 19 No. 1 (2022): SEPTEMBER, 2022; 100-108</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/21617/8613</dc:relation>
	<dc:relation>10.20956/j.v19i1.21617.g8613</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2022 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>