<![CDATA[Ovarian cysts are a disease that only affects women and attacks the ovaries. Many people don't know about this disease, including its causes, symptoms and how to prevent it. In the world of health, there are still several problems in diagnosing diseases, especially ovarian cysts. Some lay people have no knowledge about this disease and often experience difficulties due to limited doctor schedules or the availability of specialist doctors in hospitals. Many patients want to consult or find out whether there are ovarian cysts in their pregnancy. The aim of this research is to build a knowledge-based system in the medical field that uses a combination of Forward Chaining and Certainty Factor methods to diagnose ovarian cysts. The Forward Chaining method is used to find conclusions based on cause and effect using the IF-THEN rule, while the Certainty Factor is used to provide a weight value (Expert CF) that has been determined by the expert in order to get maximum results. The result of this research is an expert system application that combines the Forward Chaining and Certainty Factor methods in diagnosing ovarian cysts. This application is intended for the public by carrying out an initial diagnosis based on the symptoms that have been input, using rules from the Forward Chaining method and calculating certainty values ??using the Certainty Factor method. With this application, it is hoped that it can help people find out about the disease they are suffering from and provide the information needed to take further action.]]>
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