<![CDATA[The increasing global demand for strawberries as a high-value crop requires effective management strategies for pests and diseases that can significantly reduce yields. This research develops an expert system to diagnose strawberry pests and diseases using the Certainty Factor (CF) method, utilizing data from previous studies to improve the accuracy and reliability of the diagnosis. The system integrates symptoms and CF values from two main studies and provides treatment recommendations that can be applied to the identified problems. The results show that in the trial on powdery mildew fungus, which has 4 symptoms, it can have the highest confidence value of 0.99977848. For other diseases themselves will have different confidence values according to the calculation of the CF value of each symptom. This approach provides a valuable tool for farmers with limited access to expert consultation, helping to improve decision-making and reduce economic losses. Performance analysis of the system shows its potential to support sustainable strawberry cultivation.]]>
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