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Analysis of Factors that Influence Maternal Mortality Rates Using Generalized Poisson Regression pratiwi, Yuniar Ines; Khaulasari, Hani; Farida, Yuniar; Ferdani, Ayu
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 2, October 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss2.art2

Abstract

Maternal Mortality Rate (MMR) is the number of deaths of women within 42 days after childbirth or during pregnancy. Objective: This study aims to identify factors affecting MMR in East Java and compare the performance of the Generalized Poisson Regression (GPR) model with Poisson regression. The method used is Generalized Poisson Regression, a regression model for count data, which extends Poisson regression to overcome the problem of overdispersion or underdispersion with data derived from the East Java Health Office, including MMR as the dependent variable, as well as five variables that are thought to affect it in 38 districts/cities. The GPR model proved superior to Poisson regression with an Akaike Information Criterion (AIC) value of 239.515 to identify factors affecting maternal mortality. Factors such as delivery handled by health workers, K6 visits by pregnant women, provision of diphtheria-tetanus immunization, and obstetric complications affect MMR in East Java in 2022.