Expert System in Accuracy to Identify Gingivitis in Humans Using the Certainty Factor Method
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Abstract
Gingivitis is a common inflammatory disease of the gums, which is a condition where bacteria develop in the mouth that causes damage to the connective tissue cells that are attached to the teeth. Lack of awareness in caring for teeth will have a negative impact not only on dental health but also on the health of the body. At present many people do not know how to accurately identify gingivitis in humans so that the condition is worsened and can even cause the paralysis of the existing connective tissue. This study aims to determine the level of accuracy in identifying gingivitis by using the Certainty Factor method precisely and accurately. The data processed in this study are fifty data sourced from expert interviews at Rahmatan Lil Alamin Clinic, Padang Indonesia. There are several types Symptoms refer to gingivitis in humans. The data is obtained from the results of medical records of patients who carry out examinations in the clinic. The data will be processed to identify the type of gingivitis based on the direction of the expert. The processing steps are solving rules, determining the weight value of each symptom and calculating the Certainty Factor value. The results of the processing were continued by calculating the level of accuracy. The results of the testing of this method were that 96% of them had gingivitis, the type most often suffered by marginal gingivitis patients. Based on the signs entered by the user. The results of this test have been able to specifically identify gingivitis, using the Certainty Factor method, the results of the accuracy level obtained are quite accurate and can be recommended to help dentists improve their accuracy in identifying gingivitis in humans.
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