Expert System to Diagnose Internet Addiction Levels using Bayes Theorem Method

Abstract

The internet is one of the most popular media today by teenagers. Not a few people are very dependent on the internet so that users are addicted, the symptoms of addiction are given the name Internet Addiction. Internet Addiction is defined as a syndrome characterized by spending an enormous amount of time using the internet and not being able to control its use while online. People who show this syndrome will feel anxious, depressed, or empty when not online on the internet. The low awareness of the public about this addiction disorder is a factor in the increasing number of people, especially teenagers, who underestimate this addiction disorder and are often regarded as something natural because in this era it is indeed a time of wide open technology. Therefore there is a need for technology that helps diagnose internet addiction using the Bayes Theorem Method. In the Bayes theorem method, each symptom weight in this disorder is determined by the probability of the results of a survey or questionnaire that has been done previously as much as 50 data. tendency of individuals who are indicated to be addicted to the internet. Bayes' theorem uses a statistical approach to calculate trade offs between different decisions, using the probabilities and values that accompany a decision. The system test shows that the Bayes theorem method has an accuracy rate of 60% to diagnose the level of internet addiction experienced by teenagers..