Sujito, Langlang Gumilar, Ridho Riski Hadi, M. Rodhi Faiz, Syafriyudin, Zory Satrio Nugroho
The modern times, necessary of electrical energy can't be separated from human daily life. In order to keep an electricity demand fulfilled, it is necessary to connect the supply of electrical energy according to demand and load forecasting that will take place in the future. This research used independent variables like population, Gross Regional Domestic Product (GRDP), and City/Regency Minimum Wage (UMK) to predict a dependent variable like electricity load growth for each sector, such as household, business, industrial, and general sectors. In this study, the interpolation method is used to describe the annual data into monthly form before forecasting is carried out. The interpolation method were used a linear interpolation and quadratic interpolation. The results of interpolation with a linear regression method were used to predict a growth of electrical load. A test for accuracy a forecasting, it were used two test methods such as Mean Percentage Error (MAPE) and Root Mean Square Error (RMSE). From the results of this analysis that have been done, a forecasting with linear interpolation has MAPE values of 0.63% and RMSE 2953.87 while quadratic interpolation has MAPE values of 0.58% and RMSE 2945.77. Based on the MAPE and RMSE values, forecasting with quadratic interpolation have a better accuracy value than linear interpolation. © 2022 IEEE.
Universitas Negeri Malang, Electrical Engineering Department, Malang, Indonesia; Ist Akprind, Electrical Engineering Department, Yogyakarta, Indonesia