Expert System Design to Diagnos of Virus Infection Disease in Children with Certainty Factor Method

Sentot Achmadi, Ali Mahmudi, Anggiana Nayang Gita


Information technology that continues to grow can be utilized in the service of human life in the world of health. Infectious disease is a disease that is quite dangerous for children. Delay in treating the disease can cause more severe disease. So that a system that has the ability to diagnose diseases is needed. Expert systems are computer applications that try to adopt human knowledge to computer programs like an expert. Many expert systems have been developed including diagnosing stroke and others. In this study, the expert system was used as a tool to diagnose viral infectious diseases in children. In this study we will discuss the making of expert system applications for infectious viral infections in desktop-based children using the certanty factor (CF) method. This expert system was built to diagnose tropical diseases caused by viral infections. This system provides information about diagnosis, treatment and prevention. Methods of tracking the symptoms of each patient, matching them with existing rules, and producing a diagnosis based on the knowledge base. Knowledge based from this expert system was obtained from several pediatricians and reference books. This expert system application is designed based on desktop and MySQL database as data storage. The resulting output is the value of the possibility of child disease based on the symptoms that have been given by the user. The magnitude of the probability value is the result of calculations using the certainty factor method.


expert system, artificial intelligent, children disease, certainty factor

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