A COMPARATIVE STUDY BETWEEN THE HOLT-WINTERS MODEL AND FUZZY TIME SERIES IN PREDICTING MONTHLY ELECTRICITY CONSUMPTION: A CASE STUDY OF THE ZLITEN REGION

This study aimed to compare the performance of the Holt-Winters model and the fuzzy time series model in predicting monthly electricity consumption using monthly data for the Zliten region from January 2017 to December 2024. The study employed descriptive analysis and time series analysis methods. IBM SPSS Statistics was used to implement the Holt-Winters model, while the fuzzy time series model was implemented using fuzzy logic relationships. The efficiency of both models was evaluated using prediction accuracy measures such as MAE, RMSE, and MAPE. The results showed that both models possessed good predictive power, with the Holt-Winters additive model clearly outperforming the fuzzy time series model based on the prediction error values. The study recommended adopting the more accurate Holt-Winters additive model for forecasting future electricity consumption.