Penerapan Algoritma C5.0 untuk Prediksi Penyakit THT

Abstract

Ear, Nose and Throat (THT) disease is one type of health disorder that is commonly encountered and requires fast and accurate diagnosis. This study aims to apply the C5.0 algorithm as a classification method in predicting the type of ENT disease based on the patient's clinical symptoms. The data used in this study are medical records of 300 patients consisting of several features such as fever, ear pain, runny nose, throat pain, and swollen glands. The results showed that the C5.0 algorithm was able to produce a prediction accuracy of 89.7% and was superior to other classification methods such as CART and ID3. These findings contribute to the development of a decision support system for early diagnosis of ENT diseases automatically.