REGRESI NONPARAMAETRIK SPLINE PADA DATA LAJU PERTUMBUHAN EKONOMI DI KALIMANTAN

Abstract

The Economic Growth Rate (EGR) is an important indicator to measure the success of economic development.The welfare and progress of an economy is determined by the amount of growth shown by changes in the quantity of goods and services produced nationally. High economic growth is a goal that is expected to be achieved in a developing country. Many factors affect EGR in Kalimantan, so it is necessary to do modeling to find out the factors that significantly affect EGR. This study uses 6 factors that are suspected to influence EGR, namely the labor force participation rate, the number of large and medium industries, the average length of schooling, regional income and expenditure budgets, general allocation funds and rice productivity. The data is 2017 data obtained from the Central Statistical Agency (CSA) in 5 provinces in Kalimantan. The method used to model EGR is spline nonparametric regression and obtained the optimal knot point with the smallest GCV (Generalized Cross Validation) value of three knots. Based on the research results obtained an R2 of 82.15 percent which shows that the model formed is suitable to be used to model data patterns and there are 6 variables that have a significant effect on EGR namely labor force participation rates, number of large and medium industries, average length of schooling, regional income and expenditure budgets, general allocation funds and rice productivity.