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All Journal Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Jurnal Penelitian Komunikasi dan Opini Publik JURNAL MEDIA INFORMATIKA BUDIDARMA INTECOMS: Journal of Information Technology and Computer Science Journal of Education and Instruction (JOEAI) JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Komputer dan Informatika (JSON) Journal of Software Engineering, Information and Communication Technology Journal of Integrated and Advanced Engineering (JIAE)
Ardhian Ekawijana
Politeknik Negeri Bandung, Bandung
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Deteksi Dini Anak Disleksia dengan metode Support Vector Machine Ardhian Ekawijana; Akhmad Bakhrun; Zulkifli Arsyad
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4776

Abstract

Dyslexia is a brain disorder caused by genetics. People with dyslexia can live a normal life and even have certain advantages if they get the correct education. People with dyslexia often get the predicate stupid because teachers do not know the case of their students. Early detection of dyslexic children can be done with a series of tests so that the system can conclude that the data is dyslexic or not. Support Vector Machine is a data classification method to share dyslexia test results or not. This system is trained with test results data that are already available using the SVM method. This study uses gamification data to detect dyslexic children or not. SVM proves a good level of accuracy in predictions up to 94%.
Co-Authors Asri Maspupah Azizah Zakiah Bakhrun, Akhmad Beri Noviansyah Cholid Fauzi Didik Suwito Pribadi Eka Angga Laksana Kurniawan, M Teguh Nashirin, Wafi Khoerun noviansyah, beri Priyanto Hidayatullah, Priyanto Suprihanto Suprihanto Thamrin, Irawan Wisnuadhi, Bambang Yadhi Aditya Permana Zaman, Azzam Badruz Zulkifli Arsyad