Development of Expert System for Diagnosis of Rabbit Survivors by Using Case Based Reasoning Methods
Abstract
Rabbit is one of the animals that can not be separated from the threat of disease
that if left unchecked will have a negative impact on its health. Factors that can
make rabbits often affected by disease is the cleanliness of the cage and the food.
Some diseases that can attack rabbits include diare, scabies, and hairball. In
addition, it is rare for rabbit breeders to check their rabbits up to the vet due to
their lack of time. Sick rabbits which are not immediately given a handler will
make the disease worse and even cause death. Consequently, the development of
expert rabbit disease diagnosis system was made using the method CBR (CaseBased Reasoning). The method is a method of solving problems in finding
solutions to a new case, the system will search for solutions to old cases. In this
method there are 4 processes namely retrieve, reuse, revise and retain. Research
on developing an expert system for diagnosing rabbits using a Case-Based
Reasoning method aims to be able to help provide the first treatment of diseases
suffered by rabbits based on the similarity of the existing symptoms and knowing
the first treatment in overcoming diseases in rabbits by inputting the symptoms of
the disease in order to know the disease and handling it. The results of this system
are in the form of a diagnosis of the disease and the main solutions needed
according to the input of symptoms selected by the user. This study resulted in
testing the suitability between results from experts and applications by 83%.
Keywords: rabbit, Case Based Reasoning, expert system, rabbit disease
Downloads
Copyright (c) 2021 Luqman Affandi, Mamluatul Hani'ah, Nita Komalasari,
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright for articles published in this journal is retained by the authors, with first publication rights granted to the journal. By virtue of their appearance in this open access journal, articles are free to use after initial publication under the International Creative Commons Attribution-NonCommercial 4.0 Creative Commons CC_BY_NC.