Modeling of Maternal Mortality Risk Factors Using Negative Binomial Regression Approach in Southeast Sulawesi Province in 2022 - Alfia Mutmainah; Ruslan; Irma Yahya (Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung, 2025)
Abstract. This study aims to model the risk factors for maternal mortality in Southeast Sulawesi Province in 2022 using a negative binomial regression approach. This analysis is used to overcome the overdispersion problem in count data. The data used is secondary data obtained from the Southeast Sulawesi Provincial Health Service. The variables studied included the number of health centers, the percentage of births in health service facilities, the percentage of pregnant women who implemented the K4 program, the percentage of pregnant women who implemented the K1 program, and the number of midwives. The research results showed that the variables percentage of births in health service facilities, percentage of pregnant women implementing the K4 program, and number of midwives significantly affected maternal mortality. The negative binomial regression model illustrates that increasing the percentage of births in health service facilities and implementing the K4 program can reduce maternal mortality. On the other hand, increasing the number of midwives did not have a significant effect on reducing maternal mortality.