Geographically Weighted Lasso Method in Modeling the Gross Regional Domestic Product of the Bali-Nusra Region
DOI:
https://doi.org/10.34123/jurnalasks.v16i1.576Keywords:
GRDP, GWL, GWR, Multicollinearity, Spatial HeterogeneityAbstract
Indonesia's Central Bureau of Statistics announced that economic growth in 2020 is still in the negative zone, and the group of provinces in the Bali-Nusra region has the most negligible impact on economic growth. The value of Gross Regional Domestic Product (GRDP) measures Indonesia's economic growth. GRDP is the total added value all regional business units generate at a particular time. This research aims to apply and interpret the results of the Geographically Weighted Lasso (GWL) method for GRDP in the Bali-Nusra region. The GWL method further develops the Geographically Weighted Regression (GWR) approach by adding the Least Absolute Shrinkage and Selection Operator (LASSO) method. The GWL method simultaneously selects insignificant variables by reducing the value of the regression coefficient to zero using the LASSO method. The data used has the effect of spatial heterogeneity and multicollinearity, a prerequisite for modeling with the GWL method. Based on the analysis conducted, there are 41 different GRDP models for each district/city in the Bali-Nusra region. The resulting GWL model provides a coefficient of determination of 95.84 % so that the resulting model can be used and is considered valid.
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References
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