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Abstract

Stunting is a condition where a child’s height is under the average height of their age. Stunting will have an impact on the quality of human resources. The 2022 Indonesian Nutrition Status Survey reported that the prevalence of stunting in Indonesia reached 21.6%. This number decreased compared to the previous year. However, it remains below the government’s planned target of 14%. Therefore, appropriate methods are needed to model and identify the factors with the most significant impact on the data for each region studied. This research modeled the stunting problem using quantile regression. Quantile regression has several advantages, including the fact that it can be used on data with an inhomogeneous distribution and is not affected by outliers. The results showed that variables that had a significant effect on the prevalence of stunting using 0.95 quantile regression included babies receiving exclusive breast milk, percentage of family planning participants, percentage of households with access to adequate sanitation, low birth weight (LBW) babies, and percentage of toddlers who have Maternal and Child Health (MCH) books. It is hoped that this research can be utilized to carry out appropriate interventions to reduce the prevalence of stunting that occurs in Indonesia.

Keywords

Intervention Prevalence Quantile Regression Risk Factors Stunting

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How to Cite
Hayati, F., Nurlaily, D. ., & Hasanah, P. (2025). Modeling the Prevalence of Stunting in Indonesia Using Quantile Regression. Enthusiastic : International Journal of Applied Statistics and Data Science, 5(1), 1–8. https://doi.org/10.20885/enthusiastic.vol5.iss1.art1
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