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Nurul Khasanah, Nurul
Institut Agama Islam Negeri Ponorogo
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Journal : Computer Science (CO-SCIENCE)

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Studi Perbandingan Algoritma Random Forest dan K-Nearest Neighbors (KNN) dalam Klasifikasi Gangguan Tidur Khasanah, Nurul; Eka Saputri , Daniati Uki; Aziz, Faruq; Hidayat, Taopik
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.5522

Abstract

Sleep disorders such as insomnia and sleep apnea can significantly affect quality of life and increase the risk of chronic diseases. Early identification and classification of sleep disorders are crucial in preventing further impacts. This study aims to compare the performance of the Random Forest and K-Nearest Neighbors (KNN) algorithms in classifying sleep disorders using the Sleep Health and Lifestyle Dataset from Kaggle, which contains health and lifestyle data relevant to sleep patterns. The Random Forest and KNN algorithms were applied to classify sleep disorders into the categories 'None', 'Sleep Apnea', and 'Insomnia'. Based on the study results, the Random Forest algorithm achieved an accuracy of 89.69%, with the best performance in the 'None' category, reaching a recall of 96.08%. Meanwhile, KNN achieved an accuracy of 87.02% with K=5. Although Random Forest demonstrated superior results, challenges were still found in detecting the 'Sleep Apnea' category, where recall only reached 74.55%, likely due to data imbalance. This study shows that the Random Forest algorithm is more effective in classifying sleep disorders compared to KNN. Future research steps include data balancing and exploring other algorithms such as XGBoost to improve the performance of sleep disorder detection.
Studi Perbandingan Algoritma Random Forest dan K-Nearest Neighbors (KNN) dalam Klasifikasi Gangguan Tidur Khasanah, Nurul; Eka Saputri , Daniati Uki; Aziz, Faruq; Hidayat, Taopik
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.5522

Abstract

Sleep disorders such as insomnia and sleep apnea can significantly affect quality of life and increase the risk of chronic diseases. Early identification and classification of sleep disorders are crucial in preventing further impacts. This study aims to compare the performance of the Random Forest and K-Nearest Neighbors (KNN) algorithms in classifying sleep disorders using the Sleep Health and Lifestyle Dataset from Kaggle, which contains health and lifestyle data relevant to sleep patterns. The Random Forest and KNN algorithms were applied to classify sleep disorders into the categories 'None', 'Sleep Apnea', and 'Insomnia'. Based on the study results, the Random Forest algorithm achieved an accuracy of 89.69%, with the best performance in the 'None' category, reaching a recall of 96.08%. Meanwhile, KNN achieved an accuracy of 87.02% with K=5. Although Random Forest demonstrated superior results, challenges were still found in detecting the 'Sleep Apnea' category, where recall only reached 74.55%, likely due to data imbalance. This study shows that the Random Forest algorithm is more effective in classifying sleep disorders compared to KNN. Future research steps include data balancing and exploring other algorithms such as XGBoost to improve the performance of sleep disorder detection.
Co-Authors Afiyanto, Hendra Agus Setyawan Amelia, Mutiara Mega Amrizal Amrizal Amrizal Amrizal Ana Safitri Andi Saryoko Anggraini, Fira Anshari Anshari, Anshari Arlanda, Revilarita Aziz, Faruq azzahra, miftachul Budi Prasetyo Samadikun Cabiles, Roldan C. Cahyanti , F Lia Dwi Cahyanti, F. Lia Dwi Candra Dewi, Tinara Dani Arifudin Daniati Uki Eka Saputri dany kurniawan, muhammad Deby Marlistyawati Putri Edward, Lucyana Lucky Eka Saputri , Daniati Uki Ekasari, Surya Pandewa elis, miskiyah Fadhila Rahma, Tri Inda Faiq Ainurrofiq Fatah, Khoirul Fazrin, Bintang Maulana Firasari , Elly Hariati, Wilujeng Hartono, Rudi Haryono Setiyo Huboyo Hendri Hendri Hidayat, Taopik Hotimah Husni, Radhiatul I Ketut Artawa Ilmi, Dina Nurul Indra Gunara Rochyat Juliati Nasution, Yenni Samri Ketut Widya Purnawati Kholidah, Nur Khultsum, Umi Kurniawan, Muhamad Dicky Lestari, Sepnina Like Lusiana Pratiwi, Risca Lusmiati Anisah, Retno Mayzar, Anisa Melan Susanti, Melan Mulyani, Novi Natallia, Meyvia naufal ramadhan, ilham Ni Made Suryati Nurhasanah, Fitriani Nurhidayati, Maulida Nurhusna Okto Risdianto Manullang Pamungkas, Ragil Panjaitan, Yogi Yosua Parmilah Pryla Rochmahwati Puji Astuti Putri Anggraeni Widyastuti Qadar Hasani Ragil Pamungkas Rahmah, Aulia Ziyadatur Rahmawan, M. Rizky Rahmawati Patta, Rahmawati risqiyati, dewi Roldan C. Cabiles Rukmi, Nala Sita Saccai Srg, Mahesa Nurladuni Saputri , Daniati Uki Eka Saputri, Elly Saputri, Elsa Juni Siregar, Aldi Nur Sri Wahyuni Sukani, Amat Supono Supono Susanto, Gregorius Nugroho Taopik Hidayat Tata Sutabri Tohirin, Rozikin Tugiyono Tugiyono Uki Eka Saputri, Daniati Utami, Alika Putri Vidiati, Cory Waris Waris Waris Waris, Waris Widiastuti, Endang Linirin Wiwin Widyawati Yasmita, Septi yusuff, adisti ananda Zahra, Syifa Az