PEMODELAN DENGAN PENDEKATAN DERET FOURIER PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI NUSA TENGGARA TIMUR

Abstract

In regression analysis, there are three approaches, namely the parametric
regression approach, the nonparametric regression approach, and the
semiparametric approach. In the nonparametric regression approach developed
are truncated spline, kernel, Fourier series, and wavelet. This study, which will
be used is to use the Fourier series. The Fourier series produces sine and cosine
curves with repeated data distribution. In estimating the Fourier series to
determine the best model is to use Generalized Cross Validation (GCV) and the coefficient of determination (R2). The application of the Fourier series
nonparametric regression approach was carried out at the open unemployment
rate in East Nusa Tenggara Province. The dependent variable is the open
unemployment rate, and the independent variable is the number of poor people,
the GRDP growth rate, and the college enrollment rate. The oscillations used
were one to three oscillations, and the results obtained were the parsimony model
with the optimal GCV with three oscillations and the R2 value of 84.08%.
Keywords: Fourier Series, Nonparametric Regression, Unemployment Rate.