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).
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
