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Pemodelan Regresi Binomial Negatif Bivariat pada Data Jumlah Kematian Ibu dan Bayi di Provinsi Sulawesi Selatan Tahun 2020

ESTIMASI: Journal of Statistics and Its Application · Vol. 4 No. 1 (2023) · pp. 78–88

DOI
10.20956/ejsa.vi.25082
ISSN
2721-379X, 2721-3803
Published
2023-02-14
Publisher
Hasanuddin University
Language
en

Abstract

In general, negative binomial regression is used for univariate discrete data that is overdispersive and follows the Poisson distribution. In the real world, a case is often influenced by two discrete variables that are correlated with each other. Therefore, in this paper we will examine the regression that is influenced by two independent variables, has overdispersion properties and follows a bivariate Poisson distribution. This regression is called bivariate negative binomial regression with model parameters estimated using the Maximum Likelihood Estimation (MLE) method and Newton Raphson iterations. The formation of this model is based on the Famoye method, while in general it uses the Cheon method. Furthermore, the results of this study were applied to data on the number of maternal and infant deaths in South Sulawesi Province in 2020. The results obtained were the number of puskesmas that had a significant effect on the number of maternal deaths and the proportion of handling obstetric complications, the proportion of pregnant women implementing the K4 program, the proportion of deliveries in facilities health services, the proportion of postpartum mothers implementing the KF2 program and the number of puskesmas have a significant effect on the number of infant deaths.

Keywords

Collaboration network of the authors

31 authors · 68 co-authorship links

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  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Nasrah SirajangAffiliation unknown4
Sitti SahrimanAffiliation unknown3
RaupongAffiliation unknown2
Ika FitrianaAffiliation unknown2
Aqilah Salsabila RahmanAffiliation unknown2
Sonya SonyaAffiliation unknown2
Iis Cendrah KasihAffiliation unknown1
Rizki AdiputraAffiliation unknown1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Ratmila MammiAffiliation unknown1
Nur Alfianingsih RajaAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Riska RasyidAffiliation unknown1
Hendriete Tiur Marowi WaibusiAffiliation unknown1
Anisa AnisaSultan Ageng Tirtayasa University1
Victor LimanAffiliation unknown1
Rael Hofni TandirerungAffiliation unknown1
Anisa KalondengAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Nuralyatussa’ adaAffiliation unknown1
Muh. HadriantoAffiliation unknown1
Rita Ruth Chendra ChendraAffiliation unknown1
Abdul Fathin FawwazAffiliation unknown1
Andini Riantika Putri Amirullah AmirullahAffiliation unknown1
Hadi Siswadi Hamran HamzahAffiliation 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 Regresi Binomial Negatif Bivariat pada Data Jumlah Kematian Ibu dan Bayi di Provinsi Sulawesi Selatan Tahun 2020</dc:title>
	<dc:creator xml:lang="en">Nurhidaya L</dc:creator>
	<dc:creator xml:lang="en">Herdiani, Erna Tri</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:subject xml:lang="en">Bivariate Negative Binomial Distribution</dc:subject>
	<dc:subject xml:lang="en">Bivariate Negative Binomial Regression</dc:subject>
	<dc:subject xml:lang="en">MLE</dc:subject>
	<dc:subject xml:lang="en">Newton Rapshon</dc:subject>
	<dc:subject xml:lang="en">Overdispersion</dc:subject>
	<dc:description xml:lang="en">In general, negative binomial regression is used for univariate discrete data that is overdispersive and follows the Poisson distribution. In the real world, a case is often influenced by two discrete variables that are correlated with each other. Therefore, in this paper we will examine the regression that is influenced by two independent variables, has overdispersion properties and follows a bivariate Poisson distribution. This regression is called bivariate negative binomial regression with model parameters estimated using the Maximum Likelihood Estimation (MLE) method and Newton Raphson iterations. The formation of this model is based on the Famoye method, while in general it uses the Cheon method. Furthermore, the results of this study were applied to data on the number of maternal and infant deaths in South Sulawesi Province in 2020. The results obtained were the number of puskesmas that had a significant effect on the number of maternal deaths and the proportion of handling obstetric complications, the proportion of pregnant women implementing the K4 program, the proportion of deliveries in facilities health services, the proportion of postpartum mothers implementing the KF2 program and the number of puskesmas have a significant effect on the number of infant deaths.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2023-02-14</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/25082</dc:identifier>
	<dc:identifier>10.20956/ejsa.vi.25082</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 4, No. 1, Januari, 2023 : Estimasi; 78-88</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/25082/9335</dc:relation>
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