METODE UNBIASED RISK DITERAPKAN UNTUK PEMILIHAN OSILASI OPTIMAL DALAM REGRESI NONPARAMETRIK MENGGUNAKAN PENDEKATAN DERET FOURIER

Abstract

Regression analysis that examines the relationship between response and predictor variables without making assumptions about patterns of known data distribution is known as nonparametric regression. One of the estimators that has attracted the attention of a number of researchers in nonparametric regression is the Fourier series. The nonparametric regression approach with the Fourier series can address data that has a fluctuating distribution of changes that form sine and cosine waves. The purpose of the study is to estimate the nonparametric regression model of the Fourier series using the Unbiased Risk (UBR) method, as well as to find out the factors that affect the open unemployment rate in East Java and West Java in 2022. Selection of optimal oscillations using Unbiased Risk (UBR). The UBR method can determine the optimal smoothing parameters when the variance is known. Based on the results of the study, the best model of nonparametric regression of the Fourier series with UBR is 1 oscillation shown with a minimum UBR of  and  of 64.61%. Two variables the labor force participation rate and the life expectancy rate have a significant impact on the open unemployment rate variable in East Java and West Java, according to the findings of tests of the parameters significance conducted both simultaneously and partially.