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Pemodelan Faktor-Faktor yang Mempengaruhi Kasus Stunting di Sulawesi Selatan Menggunakan Geographically Weighted Regression

ESTIMASI: Journal of Statistics and Its Application · Vol. 5 No. 2 (2024) · pp. 240–249

DOI
10.20956/ejsa.v5i2.30142
ISSN
2721-379X, 2721-3803
Published
2024-07-27
Publisher
Hasanuddin University
Language
en

Abstract

One of the prevalent nutritional issues affecting toddlers worldwide is stunting. Several studies on stunting cases have been conducted in Indonesia. However, modeling using the Geographically Weighted Regression (GWR) method in South Sulawesi has not been carried out. This study aims to identify the variables that affect the incidence of stunting in each district in South Sulawesi based on spatial modeling using the GWR method. Data on the number of stunting cases, the pproportion of low-birth-weight infants, the percentage of under-five who are malnourished, the percentage of proper drinking water, and the percentage of poor people in South Sulawesi in 2020 were used. The results show that the GWR model has an value of 86.64%, which is higher than that of the global regression model. The factors that influence the percentage of stunting based on the GWR modeling results are the percentage of under-five who are malnourished and the percentage of proper drinking water. The findings of this study are anticipated to help the government address the issue of stunting in South Sulawesi. Early prevention may then be implemented.

Keywords

Collaboration network of the authors

34 authors · 125 co-authorship links · 3 across different organisations

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  • Universitas Halu Oleo
  • Khairun University
  • Indonesia Open University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
La NalefoAffiliation unknown2
Sitti Nur IsnianAffiliation unknown2
Siti Belinda AmriAffiliation unknown1
santi santiAffiliation unknown1
Masykur KimsanAffiliation unknown1
Rosmawaty RosmawatyAffiliation unknown1
Mardin MardinAffiliation unknown1
Muhammad Aswar LimiUniversitas Halu Oleo1
Abdi AbdiUniversitas Halu Oleo1
Wulan Maulia IsnainiAffiliation unknown1
Sudarmin SudarminAffiliation unknown1
Ramis RaufKhairun University1
Afriani UlyaUniversitas Halu Oleo1
Eko HariantoIndonesia Open University1
Fardan Rezkiawan FaidaAffiliation unknown1
Nurul AzizahAffiliation unknown1
M. Bayu MarioAffiliation unknown1
Siti Nurul Nisa’aAffiliation unknown1
Nur Fadilah ReskiAffiliation unknown1
Nurul FebriantiAffiliation unknown1
Ulfi Nurul YannatulAffiliation unknown1
Sulfikar SulfikarAffiliation unknown1
Aulia RahmaAffiliation unknown1
Ikbal IkbalAffiliation unknown1
Galih Anom Arya Zamrud ManampiringAffiliation unknown1
Faiq SyihanAffiliation unknown1
Ahmad Azhari ArifAffiliation unknown1
Jamila MustabiAffiliation unknown1
Rinduwati RinduwatiAffiliation 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://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Pemodelan Faktor-Faktor yang Mempengaruhi Kasus Stunting di Sulawesi Selatan Menggunakan Geographically Weighted Regression</dc:title>
	<dc:creator xml:lang="en">Putri, Siti Choirotun Aisyah</dc:creator>
	<dc:creator xml:lang="en">Salsabila, Afifah</dc:creator>
	<dc:creator xml:lang="en">Suardi, Shafira </dc:creator>
	<dc:creator xml:lang="en">Mutmainnah, Mutmainnah</dc:creator>
	<dc:creator xml:lang="en">Aswi, Aswi</dc:creator>
	<dc:subject xml:lang="en">Stunting</dc:subject>
	<dc:subject xml:lang="en">Spatial</dc:subject>
	<dc:subject xml:lang="en">Geographically Weighted Regression</dc:subject>
	<dc:description xml:lang="en">One of the prevalent nutritional issues affecting toddlers worldwide is stunting. Several studies on stunting cases have been conducted in Indonesia. However, modeling using the Geographically Weighted Regression (GWR) method in South Sulawesi has not been carried out. This study aims to identify the variables that affect the incidence of stunting in each district in South Sulawesi based on spatial modeling using the GWR method. Data on the number of stunting cases, the pproportion of low-birth-weight infants, the percentage of under-five who are malnourished, the percentage of proper drinking water, and the percentage of poor people in South Sulawesi in 2020 were used. The results show that the GWR model has an   value of 86.64%, which is higher than that of the global regression model. The factors that influence the percentage of stunting based on the GWR modeling results are the percentage of under-five who are malnourished and the percentage of proper drinking water. The findings of this study are anticipated to help the government address the issue of stunting in South Sulawesi. Early prevention may then be implemented.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2024-07-27</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/ESTIMASI/article/view/30142</dc:identifier>
	<dc:identifier>10.20956/ejsa.v5i2.30142</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 5, No. 2, Juli, 2024 : Estimasi; 240-249</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/30142/11860</dc:relation>
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