Monita, Resi (2023) Sistem Pakar Diagnosis Gangguan Kecemasan Menggunakan Metode Dempster Shafer. Other thesis, Universitas Islam Riau.
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Abstract
Anxiety is a vague feeling of fear that is not supported by the situation. Anxiety can be considered a disorder if it occurs continuously and cannot be controlled or treated properly. Anxiety disorders can be experienced by sufferers characterized by the emergence of excessive and persistent feelings of anxiety, restlessness, nervousness, or fear that are accompanied by certain symptoms. Anxiety disorders, if not treated properly, can interfere with the sufferer's routine. The impact of anxiety disorders can not only disrupt the sufferer's routine, but also if it continues to occur it can have an impact on the physical, emotional, cognitive, and behavior of the sufferer. To get early treatment. Therefore, an expert system was developed to help early detection so that sufferers can carry out treatment quickly and intensively. From the results of knowledge acquisition by experts, this expert system consists of 5 anxiety disorders with 22 symptoms and produces 5 rule bases represented using decision trees. The method used in this expert system is using the Dempster Shafer method to handle uncertainty while the anxiety disorder tracking method uses the forward chaining method. To facilitate users when accessing it, this system is web-based. Based on the results of the system implementation, the questionnaire value is 94%, the accuracy value is 90.9%, and the sensitivity value is 9.1%, indicating that this expert system can detect early anxiety disorders and provide treatment solutions for the disorders obtained.
Item Type: | Thesis (Other) |
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Contributors: | Contribution Contributors NIDN/NIDK Sponsor Syafitri, Nesi 9088102 |
Uncontrolled Keywords: | Dempster Shafer, Forward Chaining, Anxiety Disorders and Expert System |
Subjects: | L Education > L Education (General) T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | > Teknik Informatika |
Depositing User: | Yolla Afrina Afrina |
Date Deposited: | 09 Sep 2025 09:25 |
Last Modified: | 09 Sep 2025 09:25 |
URI: | https://repository.uir.ac.id/id/eprint/28425 |
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