Dempster Shafer Algorithm For Expert System Early Detection of Anxiety Disorders

Finanta Okmayura; Vitriani Vitriani; Melly Novalia

doi:10.24843/LKJITI.2021.v12.i02.p05

Finanta Okmayura Universitas Muhammadiyah Riau
Vitriani Vitriani Informatics Education, University of Muhammadiyah Riau Pekanbaru, Indonesia
Melly Novalia Informatics Education, University of Muhammadiyah Riau Pekanbaru, Indonesia

DOI: https://doi.org/10.24843/LKJITI.2021.v12.i02.p05

Abstract

Anxiety is an excessive anxiety disorder that is often found in psychology. Some people generally do not realize that they may have symptoms of this anxiety disorder. If ignored and continued continuously, it can interfere with one's activities, reduce academic achievement, and disrupt psychological conditions that affect their lives. This expert system for early detection of anxiety disorders is carried out using forward chaining tracing techniques to explore the knowledge base, and the inference motor is the Dempster Shafer algorithm. Dempster Shafer calculation is done by combining symptom pieces to calculate the possibility of the anxiety disorder. This anxiety disorder detection system is built on the web. Then the test is carried out by comparing the value generated by the system with the value generated by two experts. The test results prove that the value generated by the system has a similarity of 85% to the value produced by the two experts. It can be concluded that implementing the Dempster Shafer algorithm for this expert system in the early detection of anxiety disorders is feasible.

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