Forward Chaining Methods in Expert Systems in the Prevention and Treatment of Carp Diseases

Abstract

Goldfish is one of the various types of cultivated animals that are widely kept and then traded because many can be utilized from Goldfish. Farmers do not regularly check for diseases in carp, especially if farmers are still unfamiliar with the symptoms and types of diseases in carp cultivation, thus making goldfish susceptible to disease. This makes it difficult for farmers to handle diseases caused by symptoms due to limited knowledge. The limitation of experts in the field of goldfish cultivation is also one of the problems that are often encountered in various regions. This study aims to identify diseases and treatment methods in carp using the Forward Chaining method based on symptoms and to design an expert system in identifying diseases and treatment methods in carp. The data needed during this research is data on the types of symptoms and types of diseases based on symptoms in carp, symptom data and treatment data for making decisions that are sourced from carp cultivation experts from a vocational high school teacher (SMK) majoring in carp cultivation and the power obtained from the Southeast Aceh City Fisheries Service. Based on the data provided by the expert, the expert has a decision-making mode, which is to collect facts first to reach a conclusion or decision, so the Forward Chaining method can be used to conduct this research. The stages of data processing include preparing input data, expert decision tables, determining rules, conducting tracking processes, making decision trees and tracking results. The results obtained succeeded in finding the disease based on the existing symptoms and solutions and initial steps for handling goldfish diseases could be found. The results of trials conducted by comparing the data with the system that has been designed have a very good level of accuracy