Application of Multivariate Adaptive Regression Splines for Modeling Stunting Toddler on The Island of Java
DOI:
https://doi.org/10.24036/ujsds/vol2-iss3/205Keywords:
GCV, Nonparametric Regression, MARS, StuntingAbstract
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.
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Copyright (c) 2024 Dzakyyah Rahma, Nonong Amalita, Yenni Kurniawati, Zamahsary Martha
This work is licensed under a Creative Commons Attribution 4.0 International License.