The Modeling of Factors that Influence the Number of Death Cases of Infant and Toddler in Maluku Province using the Bivariate Poisson Regression Method - Haumahu, Gabriella; Djamalullail, Syarifah Fitria Amalia; Noya Van Delsen, Marlon Stivo (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia, 2024)
The number of cases of infant mortality and under-five mortality have a significant relationship. Although there are differences in age categories, it can be a measure of quality of life early in life. In this study, a bivariate Poisson regression analysis method is used which uses a pair of count data with Poisson distribution. The number of infant deaths and the number of under-five deaths are the dependent variables, while the percentage of poor people , the percentage of married women under 19 years old , the percentage of low birth weight babies , and the percentage of exclusively breastfed babies are the independent variables. Based on the results of the modeling analysis, model 2 of the bivariate Poisson regression proved to be the best model with the lowest AIC value of 123,8951. The results of the analysis at show that variable has an influence on infant mortality cases, shows that variable has a significant effect on under-five mortality cases and at shows that variable has a significant effect simultaneously on infant and under-five mortality cases in Maluku Province in 2022