Application of the Moving Average Method in Forecasting Beverage Product Sales at Teman Cerita Cafe
DOI:
https://doi.org/10.35335/jict.v16i2.271Keywords:
Beverage Business, Data-Driven Decision-Making, Moving Average, Sales Forecasting, Inventory ManagementAbstract
In the current digital era, the rapid growth of the culinary industry, particularly in the beverage sector, has created intense competition among small and medium enterprises. Café Kopi Teman Cerita in Medan is one of the businesses affected by fluctuating beverage sales, often experiencing challenges in predicting demand and managing inventory effectively due to its manual data processing system. This study aims to develop a beverage sales forecasting model using the Moving Average method to assist the café in optimizing raw material procurement and improving operational efficiency. The research was conducted by collecting historical sales data for various beverage products and applying the Moving Average technique to predict future sales trends. The evaluation results show that the forecasting model achieved satisfactory accuracy, with a Mean Absolute Error (MAE) of 10.17, Root Mean Squared Error (RMSE) of 12.26, and Mean Absolute Percentage Error (MAPE) of 20.59. These findings indicate that the Moving Average method can effectively capture sales fluctuations and produce reliable predictions for short-term demand planning. The implementation of this forecasting system is expected to help the café in making data-driven decisions, minimizing inventory discrepancies, and improving customer satisfaction. Moreover, the study provides insights into how simple yet effective analytical tools can support digital transformation and competitiveness in small-scale beverage businesses.
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