Utilization Of The Certainty Factor Method To Improve Diagnostic Accuracy In An Expert System For Diseases And Pests Of The Sugar Palm (Arenga Pinnata)
Abstract
The sugar palm (Arenga pinnata) is an economically valuable plant with various applications in food, construction, and biofuel production. However, its cultivation is often affected by diseases and pests that can reduce productivity and quality. This study aims to develop an expert system for diagnosing diseases and pests in sugar palm trees, using the Certainty Factor method to enhance diagnostic accuracy. The Certainty Factor method enables the system to incorporate uncertainty in expert knowledge by quantifying confidence levels for each diagnosis. By applying this method, the expert system provides more accurate and reliable diagnostic results, especially in cases where symptoms are ambiguous or overlap among different diseases. Designed as a web-based application, the system is easily accessible to farmers and agricultural professionals. Testing results indicate that the use of the Certainty Factor method significantly improves diagnostic accuracy, making this tool valuable for better disease and pest management in sugar palm cultivation.
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