<![CDATA[Price fluctuations of chili remain a major challenge for micro-enterprises in Indonesia, driven by seasonal patterns, weather variability, and supply distribution issues. Such uncertainty complicates pricing strategies and increases the risk of losses. This study aims to design a web-based Decision Support System (DSS) for forecasting red bird’s eye chili prices using the Triple Exponential Smoothing (TES) method. The dataset comprises daily chili price records from February 20, 2024, to February 20, 2025, collected from a local trading business in Bondowoso. The system was developed using PHP, MySQL, and XAMPP, and is equipped with table and chart visualizations to enhance interpretation. Forecast accuracy was evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate an error rate of 4.90% or an accuracy level of 95.10%, which is classified as highly accurate. These findings confirm that TES is effective in capturing trend and seasonal patterns in chili price data. In conclusion, the integration of TES into a web-based DSS demonstrates strong potential in generating precise, adaptive, and user-friendly forecasts. The system can serve as a strategic tool for micro, small, and medium enterprises (MSMEs) to minimize risks from market volatility and support data-driven decision-making in price management.]]>
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