SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA IKAN HIAS AIR TAWAR DENGAN FUZZY INFERENCE SYSTEM

Abstract

One of the main causes of failure in aquaculture activities is due to disease factors. The emergence of disease disorders in fish farming is a biological risk that must always be anticipated. The emergence of diseases in fish is generally the result of complex / unbalanced interactions between the three components in the aquatic ecosystem, namely weak hosts (fish), malignant pathogens and deteriorating environmental quality. Fish cultivators must obtain fast information related to diseases that infect their fish, and how to deal with them. In this study an expert system was created to diagnose ornamental fish disease using the media website, so that it can be used at any time without having to see a doctor / expert. Knowledge base involves 23 symptoms and 5 diseases that are common in freshwater ornamental fish, using a decision table producing 20 Rule. The inference process uses the Tsukamoto fuzzy, the modeling has 23 input variables and 1 output variable. Each input variable has 3 sets and the output variable has 5 sets. The implementation results indicate that the system built can provide diagnostic results with an 85% accuracy rate.