<![CDATA[Sales forecasting is a critical aspect of the automotive business as it influences marketing strategies, production, and inventory management. This study examines a comparison of Toyota car sales forecasts using the Single Moving Average (SMA) and Single Exponential Smoothing (SES) methods. The primary objective is to evaluate the accuracy of the SES method in predicting Toyota car sales and compare it with actual sales data. Historical sales data serve as the basis for forecasting, with the smoothing parameter α tested to obtain the best results. Forecasting with SMA demonstrates improved accuracy as the number of average periods increases. The 2-period SMA produces forecasts that are more responsive to sales trends, while the 3-period SMA provides more stable predictions without compromising accuracy. Meanwhile, the SES method with α = 0.3 delivers reasonably accurate forecasts. By applying this method, companies can make better decisions regarding Toyota car production and inventory management, ultimately enhancing operational efficiency and customer satisfaction.]]>
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