Expert System Diagnosing Diseases of Freshwater Ornamental Fish using Bayes' Theorem Method - Roindah Simalango (Institute of Computer Science, 2020)
When a fish is attacked by a disease, it will show physical changes, it can be seen from the symptoms that appear. From the visible symptoms, the type of fish disease can be identified and the treatment stage is immediately carried out so that there is no big loss. Diagnosis is the initial stage to find out the symptoms of a type of ornamental fish disease in order to be able to overcome the disease at an early stage. The purpose of diagnosis using Bayes' theorem is to help the public / ordinary people do the work of experts to diagnose computer-based ornamental fish diseases easily, quickly and the process can be repeated automatically. An expert information system is a software application that has a knowledge base for a particular domain and uses inference reasoning like an expert in solving a problem. In the design of the expert system that was built, the disease code was determined consisting of codes P001 to P0016, used as a reference for diagnosing the disease. Symptom code: G1 to G31, is the type of symptom that appears. In the testing phase, a trial was carried out on the Expert System application with the Bayes Theorem that had been built. The results of the diagnosis and the probability of the disease in ornamental fish will be searched using calculations based on the symptoms experienced by the fish. From the case example, after calculating the Bayes value, the highest cause with a percentage of 86% was caused by Aeromonas sp. and Pseudomonas sp.