Abstract
Sales forecasting is a crucial component of operational strategy and inventory management in the culinary industry, particularly for businesses dealing with raw materials that have short shelf lives. The Sate Padang Hapis business faces the challenge of unpredictable monthly fluctuations in consumer demand, which often lead to supply imbalances, overproduction, or lost profit opportunities due to stockouts. This study aims to implement and analyze the accuracy of the Single Moving Average (SMA) quantitative forecasting method in predicting Sate Padang Hapis sales volumes for June 2026. Model performance was evaluated by assessing mathematical accuracy across two time-interval variations: 3-month and 5-month moving averages. Projection error rates were rigorously measured using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) parameters. The analysis reveals that the Single Moving Average model with a 5-month interval yields projections closest to actual data, achieving the lowest error rates (MAD: 28.00; MSE: 1,304.00; MAPE: 2.28%). Implementing this forecasting model provides management with an objective basis for decision-making, enabling the effective and efficient optimization of raw material logistics and supply management.
