<![CDATA[Cilembu sweet potato exports have strong potential in international markets; however, this opportunity may lead to problems if it is not accompanied by the company’s readiness to plan shipment volumes accurately. Therefore, forecasting is needed to help the company develop more measurable estimates of shipment volumes in line with demand dynamics. This study aims to This study aims to (1) identify and analyze the historical pattern of PT XYZ’s cilembu sweet potato export shipment volumes to Singapore; (2) analyze shipment-volume cilembu sweet potato forecasting using the Moving Average (MA), Weighted Moving Average (WMA), and Exponential Smoothing (ES) methods; and (3) select the best model to support shipment-volume planning for Cilembu sweet potatoes. This study uses secondary data on shipment volumes and applies simple time-series forecasting methods, namely MA, WMA, and ES. Forecasting analysis is conducted by determining parameters through testing several alternatives and then evaluating accuracy using MAD, MSE, and MAPE. The results show that (1) the historical shipment-volume pattern tends to fluctuate and is influenced more by short-term changes than by a strong trend; (2) the selected parameters are MA(3), WMA (1–2–3), and ES with α = 0.3 because they produce the smallest error values and provide the best accuracy for forecasting the next-period shipment volume of Cilembu sweet potatoes; and (3) Exponential Smoothing (ES) is identified as the best method, yielding a forecast of 564.103 kg as the shipment volume for the next period.]]>
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