SISTEM PAKAR DIAGNOSA HAMA TANAMAN KEDELAI DENGAN METODE FUZZY TSUKAMOTO

Abstrak

Soybeans are a key ingredient in Indonesian foods such as tempeh, tofu, and soy sauce. However, pest attacks often reduce the quality and quantity of production. Delays in pest diagnosis can result in significant losses for farmers. This research aims to develop an expert system for diagnosing soybean plant pests using the Tsukamoto Fuzzy Method. This system uses various physical symptoms as input variables, such as brown spots on seeds, premature plant death, leaf epidermis damage, and the presence of larvae on stems. These symptoms are processed to identify the output variable, namely the type of pest, including: bean fly, armyworm, pod borer, shoot fly, ladybug, and stem fly.Based on testing results, this expert system has proven capable of accurately identifying the types of pests attacking soybean plants based on the input symptoms. In addition to diagnosis, the application also provides solutions in the form of in-depth information regarding pest characteristics and effective control methods.