Deteksi Dini Gangguan Kecemasan Menggunakan Metode Naive Bayes

Abstract

Anxiety is a common emotion when dealing with stress and everyday problems. Anxiety is generally normal, but becomes different if the anxiety is continuous and occurs for no apparent reason. In some cases, excessive problems fall outside the category of Anxiety. For people with anxiety disorders, the anxiety they experience appears consistently, the anxiety will be very difficult to control and accompanied by other physical symptoms. The anxiety that people experience is exaggerated in the sense that the threat they face is nonexistent or disproportionate to the response they feel. Therefore, the purpose of this research is to create an expert system application to overcome the distraction of the goal, which is named Mood. In making the Moodlify application, the Naïve Bayes method is used to predict whether a person has an anxiety disorder. The result of this research is a web-based application which is expected to be useful as a media to help in early detection of anxiety disorders. According to the results, the Moodlify application can be a tool for early detection of anxiety disorders with an accuracy rate of 81% for the Naive Bayes model.