Sistem Pakar Diagnosa Gangguan Tidur pada Anak Menggunakan Naïve Bayes
-
Bagus Dwi Kurniawan
*
Universitas Mercu Buana Yogyakarta, Yogyakarta,
Indonesia
- Mutaqin Akbar Universitas Mercu Buana Yogyakarta, Yogyakarta, Indonesia (*) Corresponding Author
Abstract
Humans have a need for sleep that can be said to be very important, especially as children begin to develop. Sleep helps children become smarter, producing hormones that boost energy storage, increase muscle stamina, agility, intelligence, cognitive function, and long-term memory storage are all positively affected by sleep. To identify sleep disorders in children, parents usually need to consult a pediatrician, which can be expensive and time consuming. With an expert system, the system can relieve and help parents in detecting sleep disorders in their children by selecting symptom options in the system, then the system will give the final result of the child's sleep disorder with the highest probability based on the symptoms presented, as well as providing the appropriate solution. This expert system uses the Naïve Bayes method, which is a simple probabilistic classification. This method uses machine learning that relies on probability calculations. The system covers 31 symptoms of child sleep disturbances as well as the types of sleep disorders studied include Sleep Apnea, Insomnia, Narcolepsy, Enuresis, Night Terror, Nightmare, and Sleepwalking. Based on testing with 20 case data from experts, the system achieved a 95% accuracy level. Although there are some expert system results that show two disturbances with one of which corresponds to the result of an expert showing one disturbence, the result is still considered "Suitable".
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