Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm

Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm

The level of patient anxiety in the Emergency Department (ED) is an important indicator that affects the diagnosis and medical management process. However, the classification of anxiety levels is often hampered by data imbalance, which can reduce the accuracy of predictive models. This study aims t...

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Bibliographic Details
Main Authors: Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan
Format: Article
Language:English
Published: Center for Research and Community Service, Institut Informatika Indonesia Surabaya 2025-07-01
Series:Teknika
Subjects:
SMOTE
Support Vector Machine
Anxiety Classification
Oversampling
Emergency Installation
Online Access:https://ejournal.ikado.ac.id/index.php/teknika/article/view/1243
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