MODELING PERCENTAGE OF POOR PEOPLE IN INDONESIA USING KERNEL AND FOURIER SERIES MIXED ESTIMATOR IN NONPARAMETRIC REGRESSION

Abstract

Poverty is a very serious problem and often faced by the countries in the world, especially developing countries. The percentage of poor people in Indonesia reached 11.47 percent in 2013. The seven provinces with the highest poverty in Indonesia are Papua, West Papua, East Nusa Tenggara, Maluku, Gorontalo, Bengkulu and Aceh. This problem is modeled using mixed nonparametric regression of Kernel and Fourier Series. The response variable of this model is percentage of poor people (y), the predictor variables that follow Kernel regression curve are Mean of Years Schooling or MYS (v 1 ) and Literacy Rate or LR (v 2 ), whereas the predictor variable that follow the Fourier Series regression curve are Unemployment Rate or UR (t 1 ). This modeling produces R 2 = 62.78%.