Abstract

This study aims to produce an expert system using the Certainty Factor (CF) Method for Diagnosing Pests and Diseases on Shallot Plants. The background of this research is to obtain information about pests and diseases. Expert System or expert system of Shallot Pests and Diseases with Certainty Factor is an expert system developed to identify pests and diseases in shallot plants. The development method used in the development of this system is the waterfall method. In the early stages of development, a needs analysis is carried out with the aim of understanding the requirements of the expert system, including the types of pests and diseases that must be identified, the associated symptoms, and the required expert knowledge. Furthermore, system design is carried out to design the system architecture and rule structure as well as the Certainty Factor weights that will be used in the diagnosis. In applying the certainty factor method, it gets a value of 46% for armyworm pests. After the design is complete, the implementation phase begins. At this stage, the expert system is designed and coded based on the designs that have been made before. The required modules, such as the inference module and the knowledge base module, are developed according to predetermined specifications. After the implementation is complete, the testing phase is carried out. using the black-box testing technique, with a score of 4.0 from the expert and 3.7 from the implementation of the beta user graph with a valid category. This test aims to ensure that the system provides an accurate diagnosis according to the symptoms observed in shallot plants.

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