Expert System to Detect Social Anxiety in Student using the Rule-based Reasoning Method

Social anxiety is a condition where a person experiences fear or anxiety about a social situation that allows a person to be watched and to be the object of attention. Fear or anxiety can be experienced by anyone, including students. The symptoms that are felt by many students are still reluctant to consult and know the extent of social anxiety, then it needs alternative media to measure the level of social anxiety and recommendations for handling it. The development of an expert system technology can be used for handling recommendations for social anxiety syndrome. Therefore, this research aims to develop an expert system which can detect and give recommendation based on Liebowitz Social Anxiety Scale (LSAS) measurement tool to determine the results of social anxiety levels. Then, the method that used in this research is Rule-based Reasoning to obtain treatment recommendations with 41 rules. The experiment result showed that from 105 testing data, the system can detect all of conditions and give the correct recommendation based on social anxiety level which detected.