PENERAPAN ALGORITMA K-MEANS DALAM PENGKATEGORIAN INSOMNIA

Abstract

Complaints of sleep disorders or insomnia are usually typified by trouble falling asleep and staying asleep, unwillingness to go back to sleep after waking, and sleep that is poor in quantity and quality. When sleep is of a high caliber, the body’s metabolism will be balanced, and vice versa. The state of the body will be affected if the sleep is of low quality, as well as affecting human emotions and the body's metabolic system. Several factors are considered to cause insomnia, including female gender, age, marital status, income, and education level. Due to the numerous variables that may considered as causes of insomnia, it is necessary to group categories in determining whether insomnia is categorized or not using a klastering technique, namely the K-Means Method. By using the K-Means method, it was found that based on the 452 data used, the result was that there were 204 data, or 45.13% belonging to the Insomnia klaster and 248 data or 54.87% belonging to the Not Insomnia klaster.