NONPARAMETRIK REGRESSION MODEL ESTIMATION WITH THE FOURIER SERIES THE FOURIER SERIES APPROACH AND ITS APPLICATION TO THE ACCUMULATIVE COVID-19 DATA IN INDONESIA

Pasarella, Muhammad Danil
Sifriyani, Sifriyani
Amijaya, Fidia Deny Tisna

BAREKENG: Jurnal Ilmu Matematika dan Terapan
Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications

The nonparametric regression model is applied to regression curves for which the regression curve is unknown. Fourier series estimation is an approach in nonparametric regression, which has high flexibility and is able to adjust to the local nature of data effectively. The purpose of the research is to obtain an estimate of the nonparametric regression model with the Fourier series approach with optimal oscillation values and the model suitability of the positive case of Covid-19 in Indonesia. Research on modeling positive cases of Covid-19 in Indonesia using nonparametric regression with the best Fourier series approach is found in the third oscillation by having a minimum GCV of 78969281 with the best model criteria R2 = 97.86% with influencing factors are the percentage of active smokers, the number of health workers, the number of health service facilities, population density and the percentage of the poor population.