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Jehad A. H. Hammad
Al-Quds Open University
Computer Science & IT

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Forecasting electrical power consumption using ARIMA method based on kWh of sold energy Gianika Roman Sosa; Moh. Zainul Falah; Dika Fikri L; Aji Prasetya Wibawa; Anik Nur Handayani; Jehad A. H. Hammad
Science in Information Technology Letters Vol 2, No 1: May 2021
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v2i1.637

Abstract

Customer demand for electrical energy continues to increase, so electrical energy infrastructure must be developed to fulfill it. In order to generate and distribute electrical energy cost-effectively, it is crucial to estimate electrical energy consumption reasonably in advance. In addition, it is necessary to ensure that customer demands can be met and that there is no shortage of electricity supply. This study aims to determine the estimated long-term electricity use with a historical Energy Sold (T1) database in kW accumulated over several periods from 2008 to 2017. The ARIMA method with the Seasonal-ARIMA (SARIMA) pattern is used in forecasting analysis. The ARIMA method was chosen because it is considered appropriate for forecasting linear and univariate time-series data. The results of this study indicate that the MAPE (%) error rate is relatively low, with a result of 7,966, but the R-Square reaches a value of -0.024 due to the lack of observational data.
Co-Authors Aji Prasetya Wibawa Anik Nur Handayani Dika Fikri L Gianika Roman Sosa Moh. Zainul Falah