Modeling the Stunting Prevalence Rate in Indonesia Using Multi-Predictor Truncated Spline Nonparametric Regression
DOI:
https://doi.org/10.34123/jurnalasks.v16i1.719Keywords:
Stunting, Prevalensi, Spline, Pemodelan NonparametrikAbstract
Introduction/Main Objectives: Stunting is the impaired growth and development that children experience from poor nutrition, repeated infection, and inadequate psychosocial stimulation. Background Problems: Based on data from the National Nutrition Status Survey (SSGI) in 2022, the prevalence of stunting in Indonesia was 21.6%, which is still above the WHO standard of below 20%. Novelty: This study was conducted with the aim of analysing the factors that influence the stunting prevalence rate in Indonesia using multi-predictor truncated spline nonparametric regression. Research Methods: The research data is secondary data taken from Health Statistics 2022 with response variables in the form of stunting prevalence. Finding Result: Based on the analysis, the best model to model the stunting prevalence rate is a multi-predictor truncated spline with three knots. In addition, it was found that four predictor variables which are the percentage of infants under 6 months old receiving exclusive breastfeeding, the average age of a mother's first pregnancy, the percentage of married women aged 15-49 using contraception, and the percentage of mothers who gave birth to a live child in the past two years and initiated early breastfeeding had a significant effect simultaneously and partially on the stunting prevalence rate in Indonesia.
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