TITLE:
Comparative Performance of Exponential Smoothing Approach in Forecasting RON 97 Fuel Price in Malaysia
AUTHORS:
Nor Hafizah Hussin, Rahaini Mohd Said, Siti Haryanti Hj Hairol Anuar, Norzailan Bin Azahari
KEYWORDS:
Fuel Price, Exponential Smoothings, Time Series Forecasting, RON97 Malaysia
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.13 No.10,
October
27,
2025
ABSTRACT: Forecasting fuel prices is a critical endeavor in energy economics, with significant implications for policy formulation, market regulation, and consumer decision-making. This study investigates the comparative efficacy of three exponential smoothing techniques: Single Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Holt-Winters Exponential Smoothing (TES), in modeling and predicting weekly RON97 fuel prices in Malaysia over the period from January 2020 to May 2025. The models were evaluated based on their predictive accuracy using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) across both in-sample and out-of-sample forecasts. The empirical results demonstrate that DES consistently yields superior performance, achieving the lowest error metrics and effectively capturing the underlying trend dynamics without the added complexity of seasonal adjustments. While TES offers a more comprehensive structure, its benefits are marginal in the absence of pronounced seasonality. SES, by contrast, exhibits limited responsiveness to trend variations. The findings underscore the suitability of DES as a robust and parsimonious forecasting tool for trend-dominated fuel price series, offering practical utility for analysts and policymakers in Malaysia’s regulated energy market. Future research may extend this framework by integrating hybrid models or exogenous economic indicators to enhance forecasting precision.