Implementation Of Forward Chaining And Case Based Reasoning (CBR) Methods In An Expert System For Diagnosis Of Rice Disease (Oryza Sativa L.) Web Based
Abstract
Rice is a plant that is very important for human survival, so this plant is widely cultivated in almost all regions of Indonesia. One of the obstacles in rice farming is pests and diseases that attack rice plants. However, rice farmers' knowledge about rice pests and diseases and their control is still lacking, especially for novice farmers. On the other hand, the number of instructors/experts regarding rice pests and diseases is still limited. Therefore, an expert system is needed which can be a problem solver in identifying pests and diseases of rice plants. In expert systems there are several methods that can be used, including the forward chaining method and case based reasoning (CBR). These two methods were chosen because they can solve problems easily, quickly and precisely. The greater the knowledge stored in the system, the more skilled the system becomes at finding a solution to a case. The result of this research is a website-based expert system using forward chaining and case based reasoning methods. The research used 10 types of rice diseases with 32 symptoms and tested the system using 20 test data resulting in an accuracy value of 95%, so that this system was declared able to be used to diagnose rice plant diseases.
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