REGRESI NONPARAMAETRIK SPLINE PADA DATA LAJU PERTUMBUHAN EKONOMI DI KALIMANTAN

Abstract

Economic Growth Rate (EGR) is an important indicator for measuring the success of an economy's 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 Bureau of Statistics in 5 provinces in Kalimantan. The method used to model the LPE is spline  nonparametric regression and the optimal knot point is 3 knot points based on the smallest Generalized Cross Validation (GCV) value of 1.208. The research results, the best model is obtained with a R2 value of 82.15 percent and a Mean Square Error (MSE) of 0.805. The results of the study provide information that the factors that influence the LPE are the level of labor force participation, the number of large and medium industries, the average length of schooling, regional income and expenditure budgets, general allocation funds and rice productivity.