Disparity of Maternal and Neonatal Death Modeling in Sumatra Region Using Geographically Weighted Bivariate Negative Binomial Regression

The Sumatra region occupies the second highest rank in terms of Maternal Mortality Rate (MMR) and Neonatal Mortality Rate (NMR) in Indonesia in 2020. Many factors are thought to have influenced these two cases, both directly and indirectly. So it is necessary to do an analysis to find out what factors influence MMR and NMR. The methods that can be used to determine these factors are Bivariate Negative Binomial Regression (BNBR) and Geographically Weighted Bivariate Negative Binomial Regression (GWBNBR). The results of the analysis show that the Deviance Information Criterion (DIC) in GWBNBR is smaller than BNBR, so GWBNBR is better than BNBR in modeling MMR and NMR in the Sumatra Region in 2020.

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Publication Details

Journal
Journal of Statistics and Data Science
Published
2025-04-25
DOI
https://doi.org/10.33369/jsds.v3i2.41285
Primary Topic
Food Security and Socioeconomic Dynamics
Type
article
Field-Weighted Citation Impact
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article

Disparity of Maternal and Neonatal Death Modeling in Sumatra Region Using Geographically Weighted Bivariate Negative Binomial Regression

Dyah Setyo Rini, Muhammad Arib Alwansyah Arib, Sigit Nugroho, Muhammad Gabdika Bayubuana
Journal of Statistics and Data Science
Food Security and Socioeconomic Dynamics
article

Disparity of Maternal and Neonatal Death Modeling in Sumatra Region Using Geographically Weighted Bivariate Negative Binomial Regression

Dyah Setyo Rini, Muhammad Arib Alwansyah Arib, Sigit Nugroho, Muhammad Gabdika Bayubuana
article en

Abstract

The Sumatra region occupies the second highest rank in terms of Maternal Mortality Rate (MMR) and Neonatal Mortality Rate (NMR) in Indonesia in 2020. Many factors are thought to have influenced these two cases, both directly and indirectly. So it is necessary to do an analysis to find out what factors influence MMR and NMR. The methods that can be used to determine these factors are Bivariate Negative Binomial Regression (BNBR) and Geographically Weighted Bivariate Negative Binomial Regression (GWBNBR). The results of the analysis show that the Deviance Information Criterion (DIC) in GWBNBR is smaller than BNBR, so GWBNBR is better than BNBR in modeling MMR and NMR in the Sumatra Region in 2020.

Journal of Statistics and Data ScienceVol. 3(2)
University of Bengkulu (ID)
Openalex Percentile: Top 88%
Food Security and Socioeconomic Dynamics
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