<![CDATA[This study aims to develop an orange harvest revenue prediction system that integrates color-based sorting technology and rule-based data analysis. With the increasing demand for oranges in Indonesia, efficiency and accuracy in the sorting process and revenue prediction are of utmost importance. The developed system utilizes the TCS34725 color sensor to classify oranges based on maturity level and employs a rule-based method to predict harvest revenue based on sorting data and external factors such as weather conditions and market prices. Field testing results indicate that this system significantly improves sorting accuracy and provides accurate revenue predictions. The implementation of this technology in the orange industry offers potential enhancements in operational efficiency and profitability. This research contributes importantly to the application of sensor technology and data analysis in agriculture, demonstrating how technological innovation can help address challenges in the orange industry and the broader agricultural sector.]]>
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