Electricity Consumption Forecasting in Indonesia Using an Artificial Neural Network
Rizka Adhiswara, Ade Gaffar Abdullah, Yadi Mulyadi
Universitas Pendidikan Indonesia
Abstract
Long-term forecasting of electricity energy consumption has become one of the main fields in the electricity sector in each country. This study aims to compare the accuracy of the results of the method used in this study with research conducted by the government to estimate electricity consumption in Indonesia. Many methods can be used to estimate electrical energy consumption such as conventional methods (exponential smoothing, ARIMA, regression), fuzzy logic and artificial neural network algorithms. The method used in this study is the Back-Propagation Neural Network (BP-ANN) algorithm. The results of this research are data on estimates of electricity consumption in Indonesia for 2019-2023. This research is expected to prove the accuracy of the Artificial Neural Network (ANN) method to estimate electricity consumption in Indonesia.
Keywords: Electriciy energy consumption forecasting; Artificial Neural Network; Back-Propagation
Topic: Electrical Engineering