Research Article
Patterns of Spatial Modeling of The Economy; Human Capital and Poverty in 60 Regions in Southern Sumatera
@INPROCEEDINGS{10.4108/eai.7-10-2021.2316809, author={Ukhti Ciptawaty and Moch. Firman Ghazali and Resha Moniyana Putri and Neli Aida}, title={Patterns of Spatial Modeling of The Economy; Human Capital and Poverty in 60 Regions in Southern Sumatera}, proceedings={Proceedings of the 4th International Conference of Economics, Business, and Entrepreneurship, ICEBE 2021, 7 October 2021, Lampung, Indonesia}, publisher={EAI}, proceedings_a={ICEBE}, year={2022}, month={4}, keywords={grdp moran i spatial autoregressive model}, doi={10.4108/eai.7-10-2021.2316809} }- Ukhti Ciptawaty
Moch. Firman Ghazali
Resha Moniyana Putri
Neli Aida
Year: 2022
Patterns of Spatial Modeling of The Economy; Human Capital and Poverty in 60 Regions in Southern Sumatera
ICEBE
EAI
DOI: 10.4108/eai.7-10-2021.2316809
Abstract
This study tests spatial concepts which is calculated in each region of the 60 regions of South Area of Sumatra by analyzing the observed spatial patterns and spatial autocorrelation. The Spatial Analytical Regression (SAR) model was chosen to analyze the cases of spatial linkage and determine how the variables meet the requirements of the model. The analysis tool uses Expletory Spatial Data Analysis with Geographic Information Systems (GIS) and Geodes to analyze the status of the proportion of poor people using Moran I, LISA, and LISA cluster map statistics in 2015. The GRDP of Sumatra's 60 regions suggests a spatial relationship. That is, there should be a clustered pattern of regions with the same characteristics. The results of the Moran I scatter plot show the division of the Moran I quadrant. Eventually, this study shows how population proportions have a significant impact on GRDP and (HDI).
