THE APPLICATION OF FORWARD CHAINING AND DETERMINISTIC FINITE AUTOMATA IN EXPOSURE SYSTEM OF INITIAL NERVE DISEASE DIAGNOSIS

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Abstract

The latest developments in the medical world use a lot of computers to help early diagnosis, prevention and treatment of a disease. This study aims to build an expert system that is used for the initial diagnosis of neurological diseases, where patients can diagnose themselves based on the symptoms they feel. The expert system method used is forward chaining, while the search flow is with Deterministic Finite Automata (DFA). This application was created using the Delphi 7.0 programming language and SQLYog. The input data are knowledge data, disease data, causes, prevention, and treatment data. The results of the consultation test with this system indicate that the system is able to diagnose neurological diseases as well as provide preventive information and recommendations that must be made based on the symptoms previously selected by the patient. With this system can help patients diagnose earlier than the symptoms of neuropathy experienced.

Keywords: Expert System, Neurological Diseases, Forward chaining, Deterministic Finite Automata, Delphi 7.0, SQLYog