Application of Multivariate Adaptive Regression Splines for Modeling Stunting Toddler on The Island of Java

Authors

  • Dzakyyah Rahma Universitas Negeri Padang
  • Nonong Amalita Universitas Negeri Padang
  • Yenni Kurniawati Universitas Negeri Padang
  • Zamahsary Martha Universitas Negeri Padang

DOI:

https://doi.org/10.24036/ujsds/vol2-iss3/205

Keywords:

GCV, Nonparametric Regression, MARS, Stunting

Abstract

Stunting is a chronic nutritional problem experienced by toddlers, characterized by a shorter body height compared to children their age.  The aim of this research is to model and determine the factors that influence Stunting on The Island of Java using Multivariate Adaptive Regression Spline (MARS).  MARS is a modeling method that can handle high-dimensional data.  The results of this study show that the best MARS model is a combination (BF=24, MI=3, and MO=2) with a minimum GCV value of 0.9475.  Based on the model, the factors that significantly influence Stunting on the island of Java are babies receiving complete basic immunization (X4), babies getting exclusive breastfeeding (X3), pregnant women getting K4 (X1), and pregnant women getting TTD (X2).  The level of importance of each variable is 100%, 81.64%, 60.38%, and 43.90%.  Based on research results, babies receiving complete basic immunization is the variable that most influences stunting on The Island of Java in 2021.

Published

2024-08-24

How to Cite

Rahma, D., Nonong Amalita, Yenni Kurniawati, & Zamahsary Martha. (2024). Application of Multivariate Adaptive Regression Splines for Modeling Stunting Toddler on The Island of Java. UNP Journal of Statistics and Data Science, 2(3), 338–343. https://doi.org/10.24036/ujsds/vol2-iss3/205

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