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All Journal INOVTEK Polbeng - Seri Informatika JURNAL ILMIAH OBSGIN : Jurnal Ilmiah Ilmu Kebidanan & Kandungan DedikasiMU: Journal of Community Service GHIDZA MEDIA JURNAL Idea Pengabdian Masyarakat Indonesian Journal of Commuity Dedication in Health (IJCDH) Duta Abdimas: Jurnal Pengabdian Masyarakat Cakrawala: Jurnal Pengabdian Masyarakat Global
Ernawati Ernawati
UNIVERSITAS MUHAMMADIYAH GRESIK
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Pengenalan Huruf Braille menggunakan Radially Average Power Spectrum dan Geometri Soffiana Agustin; Anita Sari; Ernawati Ernawati
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 1 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i1.2926

Abstract

Education is very important in the growth of children, including children with special needs such as people with visual impairments. Not only at school children can also develop their potential in learning anywhere and anytime. One of the most important learning processes is reading and writing. People with visual impairments carry out reading and writing activities using Braille. The problem is the lack of family knowledge about braille, so the activities accompanying blind children cannot be conducted. This study aims to convert braille into text, so it can make it easier for families to understand braille. The introduction of braille letters is done by extraction of frequency and spatial features. The methods proposed in this study are fast fourier transform (fft), radially average power spectrum (rapsv) and wavelets as well as several spatial features, namely local binary pattern (lbp), segmentation based on fractal analysis (sfta), first order statistics, gray level co-occurrence matrix (glcm), moment invariant and geometric features. In this study, the classification process was carried out using Bayes Net, Naïve Bayes, SVM, KNN and Random Forest. From several experiments it was found that the Random Forest classification method gave the best results. The rapsv method provides an accuracy of 93.91%, frequency feature extraction produces the same accuracy as the combination of rapsv with geometry, which is 94.04% and of all features, an accuracy of 97.18% is obtained.
Co-Authors Achmad, Abdul Kholid Agus Maulana Ramadhan Ahmad Arif Badruz Zaman Ahmad Fikri Ramadhan Ahmad Nur Kholis Ahmad Thoyyib Shofi Ainul Mufidah Ali Yusa Alkusani, Alkusani Ambarwati Eka Lestari Ana Malikah Syarifatin Andi Rahmad Rahim Anita Handayani Anita Sari Aries Kurniawan Arin Widi Kustantri Arya Setya Nugroho Atikotul Fauziyah Ayunda Sayyidatul Ifadah Bagus Hariyanto Beni Dwi Komara Citra Ayu Putriningtyas Diah Fauzia Zuhroh Diah Jerita Eka Sari Dian Agnesia Dian Indah Sari Dwi Faqihatus Syarifah Has Eka Permady Faerul Falaq Faria, Niswatun Farichatul Ainiyah Firdah Vebriyanti Ganis Irham Fanani Hanifah Rahmawati Hendriyan Aji F Heni Indapratiwi Heru Baskoro Hilda Rodhotul Ainiyah Imam Wahyu Ramadhan Indra Irawan Indro Kirono Iqnatia Alfiansyah Julianti Puji Kartika Keziah Frydha Putri Arwantini M. Gerri Setia B Mar’atus Sholihah Mas'udatus Saniyah Ma’had Wicaksono Mochammad Hafizh Maulana Moh Fachrudin Moh Faiqul Humam Moh. Adhim Moh. Dian Kurniawan Muhammad Aufa Muhammad Faris Kamaaluddin Muhammad Iqbal Ash Shidiq Muhammad Wahyu Mutahro Mutahro Nabila Anjani Eka Putri Nadia Putri Liani Pradini Nanang Khoirul Umam Ninik Anadiyah Nitha Pramestia Dhevi Noor Amirrudin Noor Amiruddin Nur Layli Fitria Nyimas Wardatul Afiqoh Parianti Parianti Pujianto Nur Romadlon Rahmat Agus Santoso Riris Dia Mariati Rizky Bagus Kuncoro Santya Dian Pratiwi Setiya Purbasari Silviana Putri Indah Sari Slamet Asari Soffiana Agustin, Soffiana Sukaris Sulastri Sulastri Suwandi, S. Suwanto Suwanto Syaiful Syaiful Tri Yuli Ardiansyah Trias Fitri Ariza Vembri Aulia Rahmi Yanuar Pandu Negoro Yusuf Hermansyah