PEMODELAN REGRESI POISSON INVERSE GAUSSIAN TERHADAP GIZI BURUK PADA BALITA DI INDONESIA

Abstract

Malnutrition is an important concern for the health and growth of toddlers because it can cause death at a very early age. The factors that influence malnutrition can be modeled with Poisson Inverse Gaussian regression is used to overcome Poisson data that has overdispersion, the variance is greater than the mean. The variables used were low birth weight babies, rural slum households, toddlers who received complete immunizations, toddlers who received exclusive breastfeeding, and the poor. This study aims to find the best model using Poisson Inverse Gaussian regression. Based on the results of the analysis, the Poisson Inverse Gaussian regression model is obtained 𝜇̂ = exp⁡(−0.0591 + 0.1060𝑋1 − 0.0061𝑋3 + 0.0384𝑋5) with variables that significantly influence the percentage of low birth weight and the percentage poor people.