Covid Symptom Severity Using Decision Tree
Naim Rochmawati, Hanik Badriyah Hidayati, Yuni Yamasari, Wiyli Yustanti, Lusia Rakhmawati, Hapsari Peni Agustin Tjahyaningtijas, Yeni Anistyasari
Abstract
Corona is a very contagious virus. In a pandemic like this, people often worry whether they are infected or not. When they cough, they often worry whether it is a sign of covid-19 or an ordinary cough. From the clinical symptoms can actually be known whether someone has Covid or not. In this study, a clinical symptom dataset will be used to classify the symptoms using a Decision Tree algorithm. The decision trees used in this research are J48 and Hoeffding Tree. Decision Tree is one of the most popular classification methods because it is easy to interpret by Humans. the prediction model uses a hierarchical structure. The concept is to convert data into decision trees or decision rules. the result of J48 were slightly better than the Hoeffding tree in terms of accuracy, precision, and recall. Meanwhile, from the tree view results, the Hoeffding Tree is simpler and the number of nodes is less than J48.