ANALISIS PREDIKSI KUALITAS TIDUR BERDASARKAN GAYA HIDUP MENGGUNAKAN METODE C4.5

Andi Sanjaya (Universitas Bina Sarana Informatika, Jakarta)
Naufal Daffa Erlangga (Universitas Bina Sarana Informatika, Jakarta)
Mohammad Badrul (Universitas Bina Sarana Informatika, Jakarta)
Fajar Mustofa (Universitas Bina Sarana Informatika, Jakarta)
Muhammad Rakha Eka Fernada (Universitas Bina Sarana Informatika)
Muhammad Pashya Mahesa Farhat (Universitas Bina Sarana Informatika, Jakarta)
Christian Nicolaus Leonardo Tambunan (Universitas Bina Sarana Informatika, Jakarta)

Jurnal Manajemen Informatika Jayakarta
Vol 6 No 2 (2026): JMI Jayakarta (April 2026)

Insomnia is a common sleep disorder characterized by difficulty sleeping, which results in poor sleep quality. This condition can lead to various negative impacts such as fatigue, decreased productivity, and mental health problems. The natural sleep cycle can be disrupted by modern lifestyle habits, for example, high levels of stress at work, a lack of physical activity, and inadequate sleep duration. To analyze and classify these lifestyle factors, a predictive model will be built using the "Sleep Health and Lifestyle Dataset" from Kaggle, which consists of variables such as sleep duration, sleep quality, physical activity level, stress level, BMI category, and blood pressure. This research is implemented using the RapidMiner software with the C4.5 data mining algorithm, which has the advantage of handling both numerical and categorical attributes.