Implementing Forward, Backward Chaining and Certainty Factor in Responsive Web-Based Expert System of Cow Disease

Abstract

This research aims to design and build expert systems of cow disease to assist farmers in identifying cattle diseases. A large number of cattle in Banyumas is not matched by the number of veterinarians, the Department of Fisheries and Livestock (DINKANAK). Banyumas records 961 cases of sick cows in 2016. This expert system is expected to assist cattle ranchers to identify cow disease and symptom-based remedies illness-symptoms. By using Inference Forward and Backward chaining which is a search method or tracking technique by using information from breeders, and Certainty Factor is used to accommodate the uncertainty of thinking of a data expert that is Doctor the process of extracting knowledge by interview. In this research system development using ESDLC (Expert System Development Life Cycle) with stages of Planning, Knowledge Acquisition, Implementation, and Evaluation. Testing is done with two approaches are Alpha Testing and Beta Testing. Alpha Testing conducted on the developer side to test the functional system using Black Box Testing method result all functional system can function well. Beta Testing is aimed at user acceptance by a Questionnaire method yields an average score of 76% or usability and the quality of system information is easy to understand.