<![CDATA[Micro, Small, and Medium Enterprises (MSMEs) in the culinary sector face challenges in sales management due to unpredictable demand fluctuations. This study aims to apply the Exponential Smoothing method as part of a time series approach to predict daily sales of fried chicken and catfish pecel, and integrate the results into a Business Intelligence (BI) framework to support operational and strategic decision-making. Primary data were collected through unstructured interviews with the business owner during Januari-December 2025, with a total of 313 operating days. Modeling used alpha (Ī±) = 0.3 selected through trial and error to obtain the best accuracy. Model evaluation used MAPE, MAE, and RMSE metrics. Results showed MAPE values of 19.33% for fried chicken (good accuracy) and 21.12% for catfish pecel (reasonably acceptable). MAE values were 3.58 and 3.25 portions/day respectively, while RMSE values were 4.42 and 4.09. Sales forecasts for January 2026 projected 23 portions/day for fried chicken and 19 portions/day for catfish pecel. Prediction results were visualized in a Business Intelligence dashboard using Microsoft Excel, producing data-driven managerial recommendations for production planning and inventory management.]]>
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