<![CDATA[This study aims to evaluate the effect of the alpha parameter on the accuracy level of the Single Exponential Smoothing (SES) method on retail inventory data. The evaluation was conducted using the MAD, MSE, and MAPE error values. The study used Toko Murni's retail inventory data from January 2025 to February 2026, consisting of white rice, cooking oil, bread flour, and 60 ml Bango sweet soy sauce. The evaluation process was carried out using a variation of alpha values from 0.1 to 0.9. The evaluation results showed that low alpha values provide a better level of prediction accuracy than high alpha values. In the white rice data, the use of alpha 0.1 resulted in a MAD value of 75.41, MSE 7167.35, and MAPE 16.86 with a prediction result of 460.43. For cooking oil, alpha 0.1 resulted in a prediction value of 75.66 with a MAPE of 18.6, while for 60 ml Bango sweet soy sauce, it resulted in a prediction of 80.51 with a MAPE of 12.79. Meanwhile, in the bread flour data, the optimal alpha value was obtained at alpha 0.2 with a predicted result of 67.19 and MAPE of 19.71.]]>
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