Early diagnosis of final-year student depression using certainty factor method

• Main Authors: Baso, Budiman, Fallo, Kristoforus, Maneno, Regolinda, Sucipto, Willi, Risald, Tey Seran, Krisantus J., Manek, Patricia Getrudis
• Format: Conference Proceeding
• Language: English
• Subjects: Confidence intervals; Data processing; Diagnosis; Expert systems; Knowledge bases (artificial intelligence); Students
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0154457

Certainty Factor is a method that defines a measure of certainty for a rule or fact, to describe the level of expert confidence in the problem at hand. The Certainty Factor method is used when dealing with problems whose answers are uncertain. In this study, the authors developed an expert system that was able to diagnose early the level of depression experienced by final semester students. Expert systems can process information based on their knowledge base so that they can solve a problem. The expert system facilitates activities by acting as an assistant because it has a knowledge base that is almost the same as the expert itself, the ability of the expert system in processing data assisted by the certainty factor method in this study can produce a fast and accurate diagnosis of the level of depression in final semester students. The results of this study indicate the application of an expert system can help in diagnosing the level of depression experienced by final semester students. The certainty factor method was successfully applied in the development of expert system applications with a system confidence level of 95%.