Assessing the indicators of economic growth in Indonesia using spatial principal components analysis

Abstract

The objective of this study is to reduce the number of indicators that affect correlated economic growth into the main component variables. The variables used Gross Regional Domestic Product (GRDP) (X1), Foreign Direct Investment (X2), Domestic Direct Investment (X3), Employment (X4), Human Community (X5), Export (X6), and Import (X7). The data used are secondary data taken from Statistics Indonesia in 2018. This study uses the Geographical Weighted Principal Component Analysis (GWPCA) with the kernel weighting used is exponential kernel weighting. The results of this study are the main component variables or new variables that can be explained about 89% of the original variables. Based on the first main component (PC1) which consists of three groups of variables that affect economic growth indicators, namely: the area of which economic growth indicators are influenced by the Human Resources variable (X5) followed by the GRDP variable (X1), the region whose indicators of economic growth are influenced by the Export variable (X6) is followed by the Import variable (X7), and the region which is an indicator of economic growth is influenced by the Import variable (X7) is accepted by the Export variable (X6).