<![CDATA[Accurate electricity consumption forecasting is crucial for infrastructure planning and grid stability, particularly in regions with rapid demand growth such as North Sumatra, Indonesia, where the residential sector accounts for over 93% of total consumption. This study conducted a comparative analysis between Holt's Linear Trend method and traditional heuristic approaches of Moving Average (MA) and Weighted Moving Average (WMA) using a simulated monthly dataset spanning 60 months with a linear growth rate of 1.5 GWh/month, a 12-month seasonal cycle with an amplitude of 25 GWh, and Gaussian noise. Holt's method outperformed MA and WMA with a Mean Absolute Percentage Error (MAPE) of 1.10%, compared to 3.68% and 3.23%, respectively. These findings provide actionable insights for energy planners and policymakers to improve the efficiency of resource allocation and grid management in North Sumatra.]]>
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