PEMODELAN REGRESI POISSON INVERSE GAUSSIAN TERHADAP GIZI BURUK PADA BALITA DI INDONESIA
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Date
2022-06
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Elfitra
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.
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Keywords
Malnutrition in toddlers, Poisson distribution, overdipersion, Poisson Inverse Gaussian Regression
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