Expert System for Detecting Diseases in Cattle Using Backward Chaining Method - Ramadani, Putri; Wahyuni, Alvi Dwi; Putra, Eka Ramadhani (Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa, 2025)
Cow is one of the livestock animals with commercial or economic value due to the sale of beef and bull semen. Livestock diseases can reduce the quality of livestock and cause a decline in sales. This research aims to help farmers recognize or identify types of diseases in cows based on visible symptoms or to prevent the risk of disease to avoid outbreaks. All data used comes from experts and a collection of documents from magazines and books related to livestock diseases. This analysis applies backward chaining in expert systems, particularly systems that process existing facts to reach conclusions. Facts are derived from physical conditions, also called symptoms. Backward chaining is a goal-based analysis that starts with an assumption of what might happen, then searches for facts (evidence) or symptoms that support (or refute) the hypothesis. The development of a web-based expert system makes it easier for farmers to access the system online. The accuracy of the expert system has been tested by stakeholders or experts, resulting in fast, accurate, and effective information. This research can assist farmers in diagnosing symptoms in livestock, and the test results can accurately detect the type of disease in livestock so that treatment can be carried out quickly.