Modeling Stunting Prevalence in Indonesia Mixed Spline Truncated and Fouries Series Nonparametric Regression

Husain, Hartina (Institut Teknologi Bacharuddin Jusuf Habibie)
Irmayani, Irmayani (Actuarial Science Department, Bacharuddin Jusuf Habibie Institute of Technology, Parepare, Indonesia)
Rahman, Andi Oxy Raihan Machikami (Data Science Department, Bacharuddin Jusuf Habibie Institute of Technology, Parepare, Indonesia)

Inferensi
Vol 7, No 3 (2024)

Stunting is a condition of failure to grow in children that occurs due to malnutrition chronic so that the child's height is shorter compared to his age. This research aims to model the factors that influence the prevalence of stunting in Indonesia based on a literature study using mixed spline truncated and fourier series nonparametric regression method. Data used is secondary data regarding the prevalence of stunting and several suspected factors influencing it, namely the percentage of the population with health insurance and the percentage of the population who smoked last month (Age ≥ 15 Years). Data was sourced from publications from the Ministry of Health and Badan Pusat Statistik (BPS) in 2022. The results show that the model combines a spline truncated component with one knot and a fourier series component with one oscillation , resulting in  a minimum Generalized Cross Validation (GCV) Value of  34.46 and an Mean Square Error (MSE) of 4.89.