Application of Forward Chaining Method, Certainty Factor, and Bayes Theorem for Cattle Disease

Abstract

Indonesia is a country that has many natural resources, especially mammals. The Papua and West Papua regions are large provinces with abundant natural resources and tremendous livestock potential. The availability of natural resources in the form of live cattle provides a great opportunity to develop animal husbandry in West Papua province. This research was conducted to create a new expert system with a knowledge base to solve the problems that occur and be useful for the community, especially cattle breeders. The current problem is the delay and lack of medical personnel in diagnosing cattle diseases, the distance that must be traveled, which is still very difficult to travel, and the lack of understanding of farmers in early handling when implications indicate animals. So, the Certainty Factor Method and Bayes Theorem with Forward-Chaining search are used to handle current problems. From the results of manual calculations, Certainty Factor Forward Chaining search is a method that has an uncertainty value of 99.84% for 3-day fever compared to Bayes Theorem Forward Chaining search with a value of 50% for worms, 50% for 3-day fever and 50% for nail rot, if applied then Certainty Factor Forward Chaining search is the most appropriate. Likewise, updating the knowledge base must be done from time to time. So that in the future, it can be compared with other methods and Android-based to facilitate current breeders.