Implementation of Certainty Factor in an Expert System for Diagnosing Pests and Diseases of Tomato Plants

Abstract

Tomatoes are a plant that is currently widely planted by farmers. Environmental factors and stable selling power are the reasons why this plant is popular with Indonesian farmers. However, that doesn't mean tomato plants don't have growth problems. Diseases such as leaf rot, fusarium wilt, bacterial wilt and leaf scorch are still the main factors inhibiting the decline in yield and quality of tomato plants in Indonesia. This is because farmers do not understand the correct diagnosis of tomato diseases. Misdiagnosis of diseases causes the use of pesticides that are not appropriate, resulting in damage or failure of tomato plants. When diagnosing tomato diseases, you need a farm advisor who can accurately diagnose tomato diseases. In this study, an expert system for diagnosing tomato plant diseases was built to determine pest and disease diagnoses and provide solutions and suggestions for existing diseases based on the selected symptoms. The method used in this expert system is certainty factor. This method was chosen because the certainty factor measures the value of a hypothesis's belief in a fact. These values are divided into two parts, namely MB and MD. The results of applying the confidence factor method to an expert system for diagnosing tomato plant diseases with examples of cases of late blight diagnosis by selecting the appropriate symptoms obtained a percentage of 97%, so it can be interpreted that the use of this method has the opportunity to solve problems in tomato plants