Expert System Using the Weighting Method for Eye Disease Symptoms

Abstract

The expert system is a branch of artificial intelligence that was developed to emulate an expert's ability to solve problems. Expert systems have been widely developed by many researchers in various fields, including the health field. Various methods have been applied to make a decision in the form of an early diagnose that is obtained accurately. This study begins with simple idea to develop an expert system which more accurate than previous research. This study applies a backward chaining method to trace the disease coupled with giving weight value to the symptoms for each eye disease. The backward chaining method works by selecting one of the diseases to explore the rules. After the disease is determined, the supporting symptoms with the highest weight of the disease will be displayed by the system to be answered by the user. Symptoms and eye diseases in this study are sourced from the eye disease reference book. The symptom weight value for each disease was obtained from giving questionnaires and direct interviews to the ophthalmologist. Giving weights value is done in order to get an early diagnosis more accurate. The early diagnosis that is obtained accurately will support the decision making for the next action that must be done. The results indicate how much the percentage of early diagnosis of eye disease that the patient may suffer based on the symptoms that are answered. The early diagnosis produced by the system is not a final decision, but rather will be used as a decision support to take further action.

Keywords

• artificial intelligence
• expert system
• backward chaining
• eye diseases
• early diagnose
• symptoms weighted value