Diagnosis Gangguan Tidur Berdasarkan Gaya Hidup Menggunakan Algoritma Naïve Bayes

Abstract. Sleep disorders are health problems that often arise due to unhealthy lifestyle patterns and are often overlooked for their impact. This study aims to help detect the risk of sleep disorders using the Naive Bayes algorithm. Data were collected through interviews and examinations, then processed with preprocessing and testing data and achieved a classification accuracy of 88.6% for three categories: Normal, Insomnia, and Sleep Apnea. These results support the application of the Naive Bayes algorithm as a supportive diagnostic method based on lifestyle factors. This finding is also expected to serve as a basis for providing lifestyle improvement recommendations to prevent the risk pf sleep disorders.