Classification Of Sleep Disorders Based on Lifestyle and Health Factors Using Random Forest and HistGradientBoosting

Sandhy Fernandez, Arif Riyandi, Sena Wijayanto, Sukmadiningtyas Sukmadiningtyas

Sari


Gangguan tidur merupakan salah satu permasalahan kesehatan yang dapat berdampak signifikan terhadap produktivitas dan kualitas hidup individu. Berbagai faktor gaya hidup dan kondisi kesehatan seperti tingkat stres, konsumsi kafein, kebiasaan olahraga, serta kondisi mental dan fisik diketahui mempengaruhi kualitas tidur seseorang. Penelitian ini bertujuan untuk mengklasifikasikan jenis gangguan tidur berdasarkan faktor-faktor tersebut menggunakan pendekatan pembelajaran mesin. Dua algoritma yang digunakan dalam penelitian ini adalah Random Forest dan HistGradientBoosting. Dataset yang digunakan terdiri dari sejumlah fitur gaya hidup dan kesehatan yang relevan, dengan target klasifikasi berupa tiga kategori utama gangguan tidur. Hasil evaluasi menunjukkan bahwa model HistGradientBoosting memberikan performa terbaik dengan akurasi mencapai 91%. Temuan ini menunjukkan potensi pendekatan pembelajaran mesin dalam membantu identifikasi dini gangguan tidur, sehingga dapat menjadi referensi untuk pengembangan sistem pendukung keputusan dalam bidang kesehatan.

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Referensi


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DOI: http://dx.doi.org/10.30811/jaise.v5i2.6983

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