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

Hartina Husain, Irmayani Irmayani, Andi Oxy Raihan Machikami Rahman

Abstract


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.

Keywords


Fourier Series; GCV; Spline Truncated; Stunting

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References


T. Beal, A. Tumilowicz, A. Sutrisna, D. Izwardy, and L. M. Neufeld, “A review of child stunting determinants in Indonesia,” Matern. Child Nutr., vol. 14, no. 4, pp. 1–10, 2018, doi: 10.1111/mcn.12617.

K. Rahmadhita, “Permasalahan Stunting dan Pencegahannya,” J. Ilm. Kesehat. Sandi Husada, vol. 11, no. 1, pp. 225–229, 2020, doi: 10.35816/jiskh.v11i1.253.

Kemenkes RI, Profil Kesehatan Indonesia 2021. 2022.

C. R. Titaley, I. Ariawan, D. Hapsari, and A. Muasyaroh, “Determinants of the Stunting of Children in Indonesia : A Multilevel Analysis of the 2013 Indonesia Basic Health Survey,” Nutrients, vol. 11, p. 1160, 2013.

V. E. Togatorop, L. Rahayuwati, and R. D. Susanti, “Predictor of Stunting Among Children 0-24 Months Old in Indonesia: A Scoping Review,” J. Obs. J. Pendidik. Anak Usia Dini, vol. 7, no. 5, pp. 5654–5674, 2023, doi: 10.31004/obsesi.v7i5.5222.

A. Murad, F. Faruque, A. Naji, A. Tiwari, M. Helmi, and A. Dahlan, “Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah,” Geospat. Health, vol. 17, no. 1, 2022, doi: 10.4081/gh.2022.1055.

S. D. Anindita, “Pemodelan Persentase Balita Stunting di Indonesia Menggunakan Regresi Nonparametrik Spline Truncated,” 2018.

H. Husain, A. F. Dewi, and A. E. Wardani, “Permodelan Prevalensi Stunting Indonesia Menggunakan Regresi Nonparametrik Spline Truncated,” J. Anal. Res. Stat. Comput., vol. 3, no. 1, pp. 1–13, 2024, [Online]. Available: https://jarsic.org/main/article/view/26/19

H. Husain, I. N. Budiantara, and I. Zain, “Mixed estimator of spline truncated, Fourier series, and kernel in biresponse semiparametric regression model,” IOP Conf. Ser. Earth Environ. Sci., vol. 880, no. 1, 2021, doi: 10.1088/1755-1315/880/1/012046.

Eubank R L, Spline Smoothing and Nonparametric Regression. New York, 1999.

M. Fariz, F. Mardianto, P. Supervisor, N. Budiantara, and M. Si, “Semiparametric Regression Model of Biresponse Using Fourier Series,” 1312.

L. Ni’matuzzahroh, “Estimator Campuran Spline Truncated, Kernel, Dan Deret Fourier Dalam Regresi Nonparametrik Pada Data Longitudinal,” 2021.

A. J. Prendergast and J. H. Humphrey, “The stunting syndrome in developing countries,” Paediatr. Int. Child Health, vol. 34, no. 4, pp. 250–265, 2014, doi: 10.1179/2046905514Y.0000000158.

Kementerian Kesehatan Republik Indonesia, “Buku Saku Hasil Studi Status Gizi Indonesia (SSGI) Tahun 2022,” Kemenkes RI, pp. 1–14, 2022, [Online]. Available: https://www.litbang.kemkes.go.id/buku-saku-hasil-studi-status-gizi-indonesia-ssgi-tahun-2021/




DOI: http://dx.doi.org/10.12962/j27213862.v7i3.20518

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