Sistem Pakar Diagnosa Penyakit Saraf Menggunakan Metode Forward Chaining dan Certainty Factor

Abstract

Neurological diseases are one of the public health problems that requires special policies in an effort to handle it so that complete data are needed regarding cause, developments and outcomes. Neurological diseases consist of various types of nerves. Most people today tend to ignore or less in response to disorders that occur in the nervous system. After all, the neurological system plays a very important role in all human activities, because if the slightest symptom or disturbance is ignored, it can have serious consequence. As technology becomes more sophisticated, therefore in the future this research is expected to help replace the role of a doctor to diagnose early symptoms in the neurological system which will be implemented in a system called an expert system.

This neurological disease diagnosis expert system is equipped with Forward channeling and Certainty factor methods. The usefulness of forward chaining in this program is to collect facts that occur to the user so that later they produce conclusions, so that users do not need to answer all the questions. By selecting the existing symptoms, you will get a conclusion that is a neurological disease that is owned by the user. The usefulness of the Certainty factor in this program is to display the level of system confidence in the diagnostic results in the form of a percentage. So that later serves to convince users when using this program.

Based on the test results, this program can provide solutions that are suitable for diseases related to the symptoms felt by the user. The results of the calculation of the Certainty factor obtained quite significant results when compared with the results of interviews with experts.