<![CDATA[Accuracy is a key point to minimize extra goods. This research aims in evaluating goods demand in a small to medium-sized enterprise. Time series was used as a research approach. The data used in this research is the demand data for powdered coffee within and outside the city for one year. This resurch begun with data collection, analysis, and finally forecasting stage using the time series method. The analysis results show that the demand data for Eyang Kakung powdered coffee SMEs has a horizontal data pattern. The time series method used is moving averages and exponential smoothing according to the data pattern classification. After forecasting, the results show MAD=56.59, MSE=4676.52, and MAPE=10.74% for demand within the city and MAD=24.34, MSE=969.46, and MAPE=4.65% for demand outside the city. Based on the forecasting results, it can be concluded that the time series method can be used as a tool to forecast demand for powdered coffee within and outside the city. By using exponential smoothing with α=0.5, it can help SMEs make decisions in preparing raw material stocks and improving production efficiency.]]>
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