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All Journal Jurnal Berkala Epidemiologi Berkala Ilmu Kesehatan Kulit dan Kelamin Jurnal Informatika dan Teknik Elektro Terapan Jurnal Pengabdian Pada Masyarakat J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Biomolecular and Health Science Journal Budimas : Jurnal Pengabdian Masyarakat Jurnal Psikiatri Surabaya (Surabaya Psychiatry Journal) Jurnal Pengabdian kepada Masyarakat Nusantara Indian Journal of Forensic Medicine & Toxicology International Journal of Environmental, Sustainability, and Social Science Jurnal Pembelajaran, Bimbingan, dan Pengelolaan Pendidikan Abdimas Indonesian Journal
Izzatul Fithriyah
Department Of Psychiatry, Faculty Of Medicine, Universitas Airlangga, Dr. Soetomo General Academic Hospital, Surabaya, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences Other

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Journal : Jurnal Informatika dan Teknik Elektro Terapan

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GWO-SVM: AN APPROACH TO IMPROVING SVM PERFORMANCE USING GREY WOLF OPTIMIZER IN INTELLECTUAL DISABILITY CLASSIFICATION Afifudin, Muhammad; Junaidi, Achmad; Sihananto, Andreas Nugroho; Fithriyah, Izzatul
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5359

Abstract

 Intellectual disability (ID) is a neurodevelopmental disorder that requires early and accurate diagnosis. This study aims to improve the efficiency of ID diagnosis using a machine learning approach. A Support Vector Machine (SVM) model optimized with Grey Wolf Optimizer (GWO) was developed and trained using data from questionnaires completed by 101 families/guardians of ID patients at RSUD Dr. Soetomo Surabaya. The features used include family history, cognitive abilities, and adaptive behaviors. The results showed that the GWO-SVM model achieved an accuracy of 95% in classifying ID patients, an improvement of 5% compared to the conventional SVM. The GWO algorithm successfully optimized the parameters in SVM, resulting in a model with the best performance. These findings indicate the potential of GWO-SVM as an effective and efficient tool for assisting in the diagnosis of ID.
GWO-SVM: AN APPROACH TO IMPROVING SVM PERFORMANCE USING GREY WOLF OPTIMIZER IN INTELLECTUAL DISABILITY CLASSIFICATION Afifudin, Muhammad; Junaidi, Achmad; Sihananto, Andreas Nugroho; Fithriyah, Izzatul
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5359

Abstract

 Intellectual disability (ID) is a neurodevelopmental disorder that requires early and accurate diagnosis. This study aims to improve the efficiency of ID diagnosis using a machine learning approach. A Support Vector Machine (SVM) model optimized with Grey Wolf Optimizer (GWO) was developed and trained using data from questionnaires completed by 101 families/guardians of ID patients at RSUD Dr. Soetomo Surabaya. The features used include family history, cognitive abilities, and adaptive behaviors. The results showed that the GWO-SVM model achieved an accuracy of 95% in classifying ID patients, an improvement of 5% compared to the conventional SVM. The GWO algorithm successfully optimized the parameters in SVM, resulting in a model with the best performance. These findings indicate the potential of GWO-SVM as an effective and efficient tool for assisting in the diagnosis of ID.
Co-Authors Abdul Khairul Rizki Purba Mustofa Indwiani Astuti Abdurachman Achmad Junaidi Adhilah, Nindy Adila Taufik Syamlan Afif Nurul Hidayati, Afif Nurul Afifudin, Muhammad Agus Hariyono Agustina Sjenny Akbar Kurniawan, Mohammad Akbar Nyong husain Akbar, Tito Robbani Alma Rossabela Setyanisa Andreas Nugroho Sihananto Andyani Pratiwi Aswin, R. Haryanto Budi Utomo Cita Rosita Sigit Prakoeswa Devi, Aprilin Krista Dhira Salsabila Diah Mira Indramaya Dina Faizatur Rahmah Dwi Murtiastutik Endang Warsiki Fatimah, Nurmawati Gilang Dokman Perkasa Hendy Margono I Gusti Ayu Indah Ardani Irwanto Ivana Sajogo Jongky Hendro Prajitno Karimah, Azimatul Khaerunnisa, Siti Khairina Konginan, Agustina Kusuma Eko Purwantari Lestari Basoeki Lia Jessica Lilik Djuari Linda Dewanti Lucky Prasetiowati Magdeline Elizabeth Carrasco Margarita Maramis, Margarita Marlina Mahajudin Monika LUKUT Muhammad Miftahussurur Muhdi, Nalini Natasya Ariesta Selyardi Putri Patria Yudha Putra Puspa Maharani Qorib, Muhammad Fathul Raden Mohamad Herdian Bhakti Rani Lauriencia Permatasari Rifat Nurwita Kusumaningtyas Rimba, Efendi Rizka Solehah S, Delwi Novita Sakina Sakina, Sakina Sari, Een Permata Sasanti Yuniar Satria Arief Prabowo Sawitri Setiawati, Yunias Sheila Maryam Gautama SOETJIPTO Sri Umijati Suksmi Yitnamurti Susanto , Joni Teisha Jediya Videlia Marantika Ummi Maimunah Vanessa Budiawan Soetioso Vinda, Igha Virzi Aliyyah Rahma Weinheimer, Anita Zara Williana Suwirman Yoshio Yamaoka Yuani Setiawati Yuliawati, Tri Hartini Yustika Izziyatu Anindita Zulfa Zahra