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Estimation of Factors Affecting Stunting Cases in West Java in 2021 Using Negative Binomial Spatial Regression

PENDUGAAN FAKTOR – FAKTOR YANG MEMENGARUHI KASUS STUNTING DI JAWA BARAT TAHUN 2021 MENGGUNAKAN REGRESI SPASIAL BINOMIAL NEGATIF

Jurnal Matematika, Statistika dan Komputasi · Vol. 20 No. 1 (2023) · pp. 41–51

DOI
10.20956/j.v20i1.26984
ISSN
2614-8811, 1858-1382
Published
2023-09-06
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

Stunting is a childhood growth and development disorder characterized by below-normal height. West Java, with its stunting rate of 24.5 percent, is one of the provinces included in the top 12 priority provinces in implementing the National Action Plan to Accelerate Stunting. Stunting cases are count data and their occurrence is rare. The analysis for the count data is Poisson regression with the assumption that equidispersion must be met. One way to overcome overdispersion is to use negative binomial regression. This study aimed to determine predictors/factors affecting stunting cases in West Java province in 2021 using negative binomial spatial regression. The data in this study comes from the publication of the West Java Health Service and the West Java Central Statistics Agency in 2021 with districts/cities as the object of observation. There is a spatial effect in the stunting data, so the spatial regression model is suitable. The results show that there is an overdispersion in the Poisson regression. The spatial effect test shows that there is a spatial dependence on the response variable and some predictors. The negative spatial autoregressive binomial is the best model with the lowest AIC value. The factors that have a significant effect are the percentage of infants aged less than six months who are breastfed, the percentage of food processing establishments that meet the requirements, and the percentage of infants with low birth weight.

Bahasa Indonesia

Stunting adalah gangguan tumbuh kembang anak yang ditandai dengan tinggi badan di bawah normal. Jawa Barat dengan angka stunting sebesar 24,5 persen merupakan salah satu provinsi yang masuk dalam 12 besar provinsi prioritas dalam pelaksanaan Rencana Aksi Nasional Percepatan Stunting. Kasus stunting merupakan data hitungan dan jarang terjadi. Analisis untuk data cacahan adalah regresi Poisson dengan asumsi equidispersi harus terpenuhi. Salah satu cara untuk mengatasi overdispersi adalah dengan menggunakan regresi binomial negatif. Penelitian ini bertujuan untuk mengetahui prediktor/faktor yang mempengaruhi kasus stunting di Provinsi Jawa Barat tahun 2021 dengan menggunakan regresi spasial binomial negatif. Terdapat efek spasial pada data stunting, sehingga model regresi spasial cocok digunakan. Hasilnya menunjukkan bahwa ada overdispersi pada regresi Poisson. Uji efek spasial menunjukkan adanya ketergantungan spasial pada variabel respon dan beberapa prediktor. Binomial autoregresif spasial negatif adalah model terbaik dengan nilai AIC terendah. Faktor yang berpengaruh nyata adalah persentase bayi usia kurang dari enam bulan yang mendapat ASI, persentase tempat pengolahan makanan yang memenuhi syarat, dan persentase bayi dengan berat badan lahir rendah.

Keywords

Collaboration network of the authors

23 authors · 53 co-authorship links

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Co-authorOrganisationJoint articles
Asep SaefuddinIPB University1
Lismayani UsmanAffiliation unknown1
Suyadi SuyadiAffiliation unknown1
Ismah IsmahAffiliation unknown1
I Made SumertajayaAffiliation unknown1
Anwar FitriantoAffiliation unknown1
Erfiani ErfianiAffiliation unknown1
Farah AbqorunnisaAffiliation unknown1
Ismail PranataAffiliation unknown1
Muhammad Nur AidiAffiliation unknown1
Aji Hamim WigenaAffiliation unknown1
Nindi PigithaAffiliation unknown1
Agus Mohamad SolehIPB University1
Indra Rivaldi SiregarAffiliation unknown1
Indra Mahib Zuhair RiyantoAffiliation unknown1
Laras SupraptiAffiliation unknown1
Salsabila FayizaAffiliation unknown1
Elke Frida RahmawatiAffiliation unknown1
Farid Yafi SuwandiAffiliation unknown1
Sachnaz Desta OktarinaAffiliation 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/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Estimation of Factors Affecting Stunting Cases in West Java in 2021 Using Negative Binomial Spatial Regression</dc:title>
	<dc:title xml:lang="id">PENDUGAAN FAKTOR – FAKTOR YANG MEMENGARUHI KASUS STUNTING DI JAWA BARAT TAHUN 2021 MENGGUNAKAN REGRESI SPASIAL BINOMIAL NEGATIF</dc:title>
	<dc:creator xml:lang="en">Djuraidah, Anik</dc:creator>
	<dc:creator xml:lang="en">Amelia, Mely</dc:creator>
	<dc:creator xml:lang="en">Anisa, Rahma</dc:creator>
	<dc:subject xml:lang="en">negative binomial</dc:subject>
	<dc:subject xml:lang="en">overdispersion</dc:subject>
	<dc:subject xml:lang="en">stunting</dc:subject>
	<dc:subject xml:lang="en">spatial regression</dc:subject>
	<dc:subject xml:lang="id">binomial negatif</dc:subject>
	<dc:subject xml:lang="id">overdispersi</dc:subject>
	<dc:subject xml:lang="id">stunting</dc:subject>
	<dc:subject xml:lang="id">regresi spasial</dc:subject>
	<dc:description xml:lang="en">Stunting is a childhood growth and development disorder characterized by below-normal height.  West Java, with its stunting rate of 24.5 percent, is one of the provinces included in the top 12 priority provinces in implementing the National Action Plan to Accelerate Stunting. Stunting cases are count data and their occurrence is rare. The analysis for the count data is Poisson regression with the assumption that equidispersion must be met. One way to overcome overdispersion is to use negative binomial regression. This study aimed to determine predictors/factors affecting stunting cases in West Java province in 2021 using negative binomial spatial regression. The data in this study comes from the publication of the West Java Health Service and the West Java Central Statistics Agency in 2021 with districts/cities as the object of observation. There is a spatial effect in the stunting data, so the spatial regression model is suitable. The results show that there is an overdispersion in the Poisson regression. The spatial effect test shows that there is a spatial dependence on the response variable and some predictors. The negative spatial autoregressive binomial is the best model with the lowest AIC value. The factors that have a significant effect are the percentage of infants aged less than six months who are breastfed, the percentage of food processing establishments that meet the requirements, and the percentage of infants with low birth weight.</dc:description>
	<dc:description xml:lang="id">Stunting adalah gangguan tumbuh kembang anak yang ditandai dengan tinggi badan di bawah normal. Jawa Barat dengan angka stunting sebesar 24,5 persen merupakan salah satu provinsi yang masuk dalam 12 besar provinsi prioritas dalam pelaksanaan Rencana Aksi Nasional Percepatan Stunting. Kasus stunting merupakan data hitungan dan jarang terjadi. Analisis untuk data cacahan adalah regresi Poisson dengan asumsi equidispersi harus terpenuhi. Salah satu cara untuk mengatasi overdispersi adalah dengan menggunakan regresi binomial negatif. Penelitian ini bertujuan untuk mengetahui prediktor/faktor yang mempengaruhi kasus stunting di Provinsi Jawa Barat tahun 2021 dengan menggunakan regresi spasial binomial negatif. Terdapat efek spasial pada data stunting, sehingga model regresi spasial cocok digunakan. Hasilnya menunjukkan bahwa ada overdispersi pada regresi Poisson. Uji efek spasial menunjukkan adanya ketergantungan spasial pada variabel respon dan beberapa prediktor. Binomial autoregresif spasial negatif adalah model terbaik dengan nilai AIC terendah. Faktor yang berpengaruh nyata adalah persentase bayi usia kurang dari enam bulan yang mendapat ASI, persentase tempat pengolahan makanan yang memenuhi syarat, dan persentase bayi dengan berat badan lahir rendah.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2023-09-06</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/26984</dc:identifier>
	<dc:identifier>10.20956/j.v20i1.26984</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 20 No. 1 (2023): SEPTEMBER, 2023; 41-51</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/26984/10267</dc:relation>
	<dc:relation>10.20956/j.v20i1.26984.g10267</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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