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Observational analysis reveals improved diagnosis of chicken diseases in farming communities, suggesting enhanced productivity.
This study aims to design and develop a web-based expert system for diagnosing chicken diseases, with a particular focus on colibacillosis, in East Sumba Regency. Utilizing forward chaining and certainty factor methods, the system is designed to generate diagnostic results based on user-input symptoms. Farming communities in East Sumba often rely on traditional practices, which can delay decision-making and adversely affect both poultry health and farmers’ economic stability. The proposed expert system is intended to enable farmers to quickly and effectively access information on early disease symptoms and preventive measures. Additionally, this research seeks to enhance farmers’ knowledge of poultry diseases, thereby reducing chicken mortality rates caused by infections. The integration of information technology into poultry farming is expected to improve efficiency and productivity within the agricultural sector in the region.
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Praing et al. (2025) studied this question.
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