<![CDATA[Corn is an important commodity in Indonesia after rice and has great potential to be developed as a primary food source. However, corn productivity is often disrupted by pests and diseases. Farmers often have difficulty in identifying and overcoming these problems due to limited knowledge and access to appropriate solutions. This study develops an Expert System for Diagnosing Corn Plant Diseases using the Certainty Factor (CF) method to assist farmers in diagnosing and overcoming pest and disease problems in corn plants. The Certainty Factor method is used to measure the level of expert confidence in the relationship between observed symptoms and the likelihood of disease occurring. This system is designed to provide a diagnosis based on symptom input provided by the user, with a confidence level calculated using a combination of CF values from the inputted symptoms. In testing this system, several cases of corn disease diagnosis were tested using the collected symptom data. The results of system testing on users through the User Acceptance Test (UAT) showed a very good level of acceptance, with a percentage of 94.75%. This system is expected to be an effective tool for corn farmers in increasing their crop productivity in a more efficient and accurate way. Thus, this system has proven to be effective as a tool for farmers to identify and overcome corn plant disease problems more precisely and efficiently.]]>
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