Oral ulcer is a condition that occurs around the oral cavity that can be caused by several factors such as fungi, bacteria, viruses, anti immune, and allergies. The problems are symptoms of oral ulcer between diseases in the same category have a high similarity that required knowledge and expert experience to diagnose the disease. Based on these problems, researchers designed a system of oral ulcer experts who have expert knowledge to obtain a diagnosis of oral ulcer along with medical treatment required by the patients. The method used in the knowledge base of this expert system is bayessian network with PHP programming language and using mySQL database. Based on the results of functional testing using blackbox test method obtained all functions can run well and in accordance with the design. While the accuracy test obtained the best accuracy of 86.13% through 3 experiments with different variations using 23 test data. With a fairly high accuracy results then the oral disease expert system using Bayessian network method is concluded to have good performance.
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