| dc.description.abstract | A producer, both a provider of goods and a service provider, certainly has the initiative to produce its products according to consumer demand so as to obtain maximum profit. To achieve this, the business must be able to determine the planning of the number of units of goods to be sold. Proper forecasting of these plans will prevent product returns. Royal's Bakery is an MSME engaged in the food sector, especially stuffed sweet bread. Products from Royal's Bakery are distributed to four stores in Medan, namely Toko JJ, Toko Risma, Toko Amos, and Toko Lin. The distribution of stuffed sweet buns is carried out every 3 days with the same quantity of products each period. The quantity of each product is 15 pieces to Toko JJ and Toko Amos, and 20 pieces to Toko Risma and Toko Lin. The determination of the same product continuously like this certainly creates a problem, namely the return of bread variant products because they do not match consumer interests. Solving these problems is done by forecasting the demand for bread in the next period. The forecasting method used is Single Exponential Smoothing based on the pattern of bread demand data in the previous period for the last 5 months. The results of forecasting the demand for JJ, Risma, Amos, and Lin store bread for Chocolate, Papaya, Coconut, and Donut products in order are 14, 11, 12, 14, 19, 19, 16, 15, 15, 18, 18, 14, 11, 12, and 15. Then, the next step is to test the error of the forecasting results using Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The MAPE value for each type of bread is below 20%, the MSE value for each type of bread is below 4, and the RMSE value for each type of bread is below 2. | en_US |
