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All Journal JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi JMM (Jurnal Masyarakat Mandiri) SINTECH (Science and Information Technology) Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMATICS JURIKOM (Jurnal Riset Komputer) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Informatika Global Journal of Information Systems and Informatics Prosiding Seminar Nasional Multidisiplin Jurnal Sistem Informasi dan Informatika (SIMIKA) Vocatech : Vocational Education and Technology Journal Jurnal Sistem Komputer dan Informatika (JSON) At-Thullab : Jurnal Pendidikan Guru Madrasah Ibtidaiyah Jurnal Inovasi Penelitian Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pengabdian kepada Masyarakat Journal of Education Research Indonesian Community Journal Edu Research : Jurnal Penelitian Pendidikan Inspirasi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Media Bina Ilmiah Journal of Research Applications in Community Services AL-UMRON: Jurnal Pengabdian kepada Masyarakat E-Amal: Jurnal Pengabdian Kepada Masyarakat Almantiq Jurnal Teras Pengabdian Masyarakat NAWASENA BHAKTI
Ita Aristia Sa'ida
Universitas Nahdlatul Ulama Sunan Giri
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Optimization of Sleep Disorder Classification Using ANN with Multi-Method Feature Selection Kharisma, Devi Nova; Prastya, Ifnu Wisma Dwi; Saida, Ita Aristia
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1473

Abstract

Sleep disorders are health problems that can affect quality of life and have the potential to increase the risk of various chronic diseases. Therefore, a computational approach is needed to accurately and efficiently classify sleep disorders. The ANN model used has a two-layer hidden architecture with 128 and 64 neurons, respectively, and uses the ReLU activation function, equipped with a dropout layer to reduce overfitting. Three neurons with a softmax activation function make up the output layer, which produces probabilities for every class. To improve model performance, three feature selection methods were compared, namely Chi-Square, Information Gain, and Pearson Correlation. The test results showed that the ANN model without feature selection produced an accuracy of 89.3%. After feature selection, the model's performance improved significantly. The Chi-Square method produced 8 selected features with the highest accuracy of 97.3%, followed by Information Gain with 5 features and an accuracy of 97.3%, and Pearson Correlation with 3 features and an accuracy of 88.0%. The results of this study demonstrate that selecting appropriate features can significantly enhance an ANN's ability to categorize sleep problems. The proposed approach is expected to be a reference in the development of a more accurate sleep disorder diagnostic aid system.
Co-Authors Abdul Faqih Abidin, Muhammmad Zaenal Afril Efan Pajri Agus Afriliyanto agustian, rifan Ainu Zuhriyah Amalia Nur Laily APRILLIA, YUSIFA Audytra, Hastie Ayu Mauliana Intahaya Bakti Putra Pamungkas Ceisa Santi, Nirma Devi Dwi Nuraliza Diah Anggraini, Diah Diah Fitriani Dirgantoro, Guruh Putro Dirgantoro, Guruh Putro Dirgantoro Dwi Issadari Hastuti Eka Asfira Eli Widyawati, Reza Elsa Azia Ulhaq Fajar Nawulansih, Dewi Febby Refindha Aftha Harianto Festian Cindarbumi Guruh Putro Dirgantoro Ifnu Wisma Dwi Prastya Jauhar Vikri, Muhammad Kharisma, Devi Nova Kurniawati, Naning M. Iqbal Tawakkal MARATUS SHOLIHAH, SITI Mochamad Nizar Palefi Ma’ady Muarofah, Isna Ayu Muhammad Adib Asrori Muhammad Zaenal Abidin Mula Agung Barata Nawafila Februyani Niken Sukmawati Nurul Huda Prabowo, Affan Agung Prastya, Ifnu Wisma Dwi Sahri Sahri Sahri Sahri Salma, Elok Salma Nabila Sanjaya, Ucta Pradema Santi, Nirma Ceisa Saputra, Agus Bima Septiana, Nailus Saidah Anindia Shafa Kirana Aralia Sholihah, Nurul Maratus SITI CHOLIFAH Siti Cholifah Siti Shoimah Sunu Wahyudhi Taufiq Hidayat Tawakkal, M. Iqbal Wulan, Diah Nawang Wulandari, Devi Ayu Zakki Alawi Zeti Novitasari