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This study aimed to know the prediction of rice sales for Employee Cooperatives Republic of Indonesia Bina Warga Benjeng in the following month. Rice sales are often difficult to predict market demand. When consumer demand increases, rice supplies sometimes suffer from shortages. If consumer demand decreases, stock builds too much and results in a decrease in rice quality. In order for the rice sales process to run smoothly, it is necessary to have a sales prediction so that there are no excesses or shortage in rice supplies. The method of discussion used to predict in this study using the Single Moving Average method which is a prediction method that uses new actual data requests to raise the predictive value of the next month’s demand. The best results were using the Single Moving Average methods using rice sales data variant 25 kg variant were successfully implemented with an RMSE value of 9.3% which means this prediction accuracy of 90.7% accurate.

The restaurant industry in Indonesia has experienced significant growth, driving the need for data-driven strategies to remain competitive. This study aims to apply and compare time series methods in forecasting sales at "Nasi Goreng Bacot" restaurant. The methods used are Simple Moving Average (SMA), Weighted Moving Average (WMA), and Single Exponential Smoothing (SES), with a focus on sales data from the year 2023.The research results indicate that SMA provides the most accurate predictions, with a Mean Absolute Error (MAE) value of 296.67, Mean Squared Error (MSE) of 129055.6, and Mean Absolute Percentage Error (MAPE) of 3.02%. WMA and SES, although useful in certain data conditions, show higher error rates in this case. This study confirms the effectiveness of SMA in the context of stable and less fluctuating restaurant sales data. With these results, restaurants can plan their inventory of raw materials and workforce more efficiently, reduce waste, and improve customer satisfaction.      

Sprite drink is a soda drink that is very popular among all groups. Demand is uncertain and always changes from time to time, making product availability difficult to control and often causes overstock or stockout problems. Therefore, inventory control is needed, which can be done by forecasting, determining safety stock and good re-order points. To obtain effective and efficient planning, the number of orders must be based on the number of past mass requests so as to reduce the occurrence of overstock or stockouts. With the problems experienced by PT. XYZ, the forecasting method used is the time series forecasting method. In this case, the time series methods used are Simple Average, Single Moving Average and also Single Exponential Smoothing. After carrying out several calculations, we obtained a Mean Absolute Centage Error (MAPE) value of 49.379%, a Mean Absolute Deviation (MAD) of 2297.145, a Root Mean Squared Error (RMSE) of 2912.495 and also a Mean Squared Error (MSE) of 8,482 .628 and forecasting results of 4504 pcs every month. Based on the calculation results, the proposal given is to reorder Sprite 250ML when the inventory in the warehouse reaches 1548 pcs with a safety stock of 540 pcs.