PEMODELAN KASUS KEMISKINAN DI JAWA TENGAH MENGGUNAKAN REGRESI NONPARAMETRIK METODE B-SPLINE - Anisa Septi Rahmawati; Dwi Ispriyanti; Budi Warsito (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2017)
Poverty is one of the diseases in the economy, so it must be cured or at least reduced. According to BPS (2016), poor people are people who have an average expenditure per capita per month below the poverty line. The poverty line in Central Java in 2016 amounted to Rp 317 348, - per capita per month. In 2016, the average level of poverty in the Java Island, Central Java province placed as the second highest after DIY. Many factors are thought to affect the level of poverty. In this study, the predictor variables used are the rate of economic growth (X1), unemployment rate (X2), and education level above high school to (X3). This study aims to obtain a model of the relationship between the factors that affect poverty on the percentage of poor and calculate the predictions. The method used is B-spline nonparametric regression. Nonparametric approach are used if the function of previous data is unknown. The best B-spline model depends on the determination of the optimal knots point having a minimum Generalized Cross Validation (GCV). In this study, the best B-spline model obtained when the order of X1is 2, the order of X2 is 2, and the order of X3 is 2. The knots obtained in X1 at the point 4,51273, X2 at the point 3,60626, and X3 at point 11,4129 and 16,2481 with GCV value of 9,79353. Keywords: Poverty, Nonparametric Regression, B-Spline, Generalized Cross Validation