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All Journal International Journal of Artificial Intelligence and Robotic Technology (IJAIRTec)
Fuad Fahmi
Prodi Sistem Informasi, STMIK Pringsewu, Lampung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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XPERT SYSTEM FOR DIAGNOSING DISEASES IN BETTA FISH BASED ON ANDROID Mardiyanto Mardiyanto; Fuad Fahmi
International Journal of Artificial Intelligence and Robotic Technology (IJAIRTec) Vol. 1 No. 2 (2021): International Journal of Artificial Intelligence and Robotic Technology (IJAIRT
Publisher : International Journal of Artificial Intelligence and Robotic Technology (IJAIRTec)

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Abstract

Betta fish are in demand and bred by the community. Based on their habitat, betta fish are in swamps, rivers, and lakes. In Indonesia, many are found in various areas such as Kalimantan, Sumatra and others. Betta fish is one of the freshwater fish which has its own uniqueness and many types, both in terms of color and shape. Some of them have bright, dark and exotic colors. Many novice breeders of betta fish are just starting their business and they find it difficult when their pet betta fish get sick. Diseases found in ornamental fish, especially betta fish, are more quickly prevented and treated if the Betta fish cultivators know in advance what diseases are attacking their fish. Therefore, a research is needed which makes it easier for novice breeders of betta fish to find out early about what diseases attack their fish before they jump into betta fish breeders. This method used the forward chaining method. In order for betta fish farmers to detect diseases more quickly, we tried to create a program to detect betta fish diseases using an expert system. This expert system also aims to provide preventive solutions to these fish so that breeders can get a satisfactory harvest. It also diagnoses diseases in fish. After these symptoms are detected, the disease, symptoms and treatment will be found.
Co-Authors Mardiyanto Mardiyanto