Comparison Forecasting Methods for Electrical Energy Demand: In Case Study Luggage Manufacturing Industry

In the luggage manufacturing industry, electrical power demand is necessary for production and electricity cost, which can be predicted in advance for electricity usage and electricity demand, allowing for future production planning. This research presents a comparison of methods for forecasting electricity demand in the luggage manufacturing industry. The electricity consumption data from July 2020 to June 2024 is used to compare the forecasting methods of the decomposition method and simple exponential smoothing, which can effectively forecast using seasonal data and data fluctuations. It was found that factoring forecasting is more appropriate than simple exponential smoothing. When comparing the mean absolute percentage error (MAPE) values of both methods, they are 1.37 and 2.39, respectively. The electric energy variable data has less error because it includes trend variables (T), seasonal variation (S), cyclical variation (C), and irregular variation (I). The factored forecast data, when used to forecast the electric energy demand for the 12-month period from July 2024 to June 2025, revealed a high electric energy value, necessitating the planning of future production. Therefore, forecasting electricity demand in the luggage manufacturing industry will help forecast and plan energy use more efficiently.