Integration of AHP and certainty factors to optimize chicken disease diagnosis
Keywords:
Analytical hierarchy process, Certainty factor, Chicken, disease, OptimizationAbstract
Chicken farmers, especially beginners, often lose money because they are not aware of the diseases of their livestock. Diagnosis of chicken diseases must be carried out appropriately to increase the productivity of poultry farms. The failure of rapid and precise disease discovery is often due to a lack of diagnostic tools and veterinary expertise. The Analytical Hierarchy Process (AHP) and Certainty Factor (CF) methods are used to build an expert system to optimize the diagnosis of chicken diseases. The Analytical Hierarchy Process (AHP) determines the weight of criteria based on their level of importance, while the Certainty Factor (CF) measures the level of confidence based on the symptoms found. By combining these two approaches, the system is able to produce more structured, measurable, and based diagnoses based on quantitative data and expert expertise. The test results show that the system to be built is very accurate in providing diagnosis recommendations based on symptoms and key criteria. The purpose of this study is that farms and veterinarians will utilize this system to better handle diseases, reduce misdiagnoses, and strengthen the poultry farming sector as a whole.
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