Data optimization on the accuracy of forecasting electricity energy sales using principal component analysis based on spatial

This paper focuses on the accuracy of forecasting with various numbers of variables to optimize the data held. The initial stage of this research is the division of clusters using the hierarchical clustering method to divide 24 administrative regions into 6 clusters, and to increase the accuracy of forecasting using principal component regression. Based on the results obtained, it can be seen that the MAPE values vary in each cluster.