COMPARING GAUSSIAN KERNEL AND QUADRATIC SPLINE OF NONPARAMETRIC REGRESSION IN MODELING INFECTIOUS DISEASES - Adityaningrum, Amanda; Ladjali, Sri Indriani; Djakaria, Ismail; Yahya, Lailany; Payu, Muhammad Rezky Friesta; Nashar, La Ode; Jusuf, Herlina (PATTIMURA UNIVERSITY, 2023)
The regression curve for nonparametric regression is assumed to belong to some infinite-dimensional collection of functions, which allows great flexibility in the form of the curve. This research intends to compare the Gaussian Kernel and Quadratic Spline regressions in four infectious diseases in Indonesia by 2021. The data used is secondary data from the Central Bureau of Statistics and the Ministry of Health, Indonesia, and the sample consists of four infectious diseases in Indonesia by 2021 (Tuberculosis, Diarrhoeal, Pneumonia, and COVID-19). Considering the correlation value, it was found that the independent and dependent variables of the four infectious diseases are all highly correlated (r values are more than 0.7). Furthermore, the scatter plots for four infectious diseases do not follow a particular pattern; due to this, parametric regression cannot be used to analyze the data. Therefore, nonparametric regression was applied in this research . According to the analysis, the Gaussian Kernel is the best regression technique for modeling four infectious diseases in Indonesia by 2021, which its R2 values are 99.85% (Tuberculosis), 100% (Diarrhoeal), 99.91% (Pneumonia), and 99.99% (COVID-19).