PENERAPAN METODE ALGORITMA SVM (SUPPORT VECTOR MACHINE) UNTUK KLASIFIKASI PENDERITA PENYAKIT GASTROESOPHAGEAL REFLUX DISEASE: APPLICATION OF SVM (SUPPORT VECTOR MACHINE) ALGORITHM METHOD FOR CLASSIFICATION OF GASTROESOPHAGEAL REFLUX DISEASE PATIENTS - Teuku Ferynanda Ramadhan; Asrianda; Risawandi (LPPM Universitas Abdurrab, 2025)
Gastroesophageal Reflux Disease (GERD) is a digestive disorder caused by the backflow of stomach acid into the esophagus, with symptoms that often resemble those of other conditions, making diagnosis challenging. This study aims to implement the Support Vector Machine (SVM) algorithm to develop a classification system for GERD patients based on clinical symptom data, including chest pain, swallowing disorders, regurgitation, and others. The research was conducted at Sakinah General Hospital in Lhokseumawe City using patient data from the 2020–2023 period. The classification system was designed through a series of stages including data preprocessing, normalization, and the application of a polynomial kernel in the SVM algorithm. The results demonstrate that the SVM algorithm achieved an accuracy of 82.5% and an F1-score of 58.3%, indicating a strong classification performance in distinguishing between GERD and non-GERD patients, and suggesting its potential as an effective diagnostic support tool for medical professionals.