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All Journal JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Technomedia Journal DoubleClick : Journal of Computer and Information Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informasi dan Komputer Jurnal Teknologi Terpadu Generation Journal JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pemberdayaan Komunitas MH Thamrin J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika dan Rekayasa Komputer
Rozikin, Chaerur
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Journal : Jurnal Informatika dan Rekayasa Komputer

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Pendeteksi Bahasa Isyarat Menggunakan TensorFlow dengan Metode Convolutional Neural Network Saputra, Reza Aditya; Ryansyah, Eddy; Setiawan, Fikri Maulana; Rozikin, Chaerur
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 5 No 2 (2025): JAKAKOM Vol 5 No 2 SEPTEMBER 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2025.5.2.2386

Abstract

Sign language recognition plays a vital role in facilitating communication for individuals with hearing impairments. This study proposes a Convolutional Neural Network (CNN) model trained to recognize patterns in sign language images with the aim of improving the accuracy and efficiency of sign language recognition systems. The model was trained in two stages with the first training session achieving a validation accuracy of around 63%, while the second training session yielded an impressive validation accuracy exceeding 92% at epoch 29. This significant improvement demonstrates the model’s ability to effectively learn and generalize complex patterns in sign language images, signaling its potential for practical applications in sign language interpretation. The high accuracy achieved by the CNN model demonstrates its suitability for use in a variety of real-world scenarios, such as assistive technology for the deaf community or automation systems requiring hand gesture recognition. Thus, the trained CNN model has the potential to be a valuable tool in improving the accessibility and efficiency of communication for individuals who rely on sign language.
Co-Authors Ali Ridha, Azhari Alifa, Rizal Fahmi Apriade Voutama Aries Suharso Arip Solehudin Armeilia, Rida Aurelly Claudia Budianto, Theresia Ayu Syaharani, Maesha Badriah, Siti Eddy Ryansyah Eka Purnama, Karolina Enri, Ultach Fahlevi, Raihan Fahmi, Ikbal Fajar Estu Nugroho, Muhammad Fatoni, Hilman Fauzi, Ihsan Garno, G. Hafizh Ridwan, Muhammad Holiyanti, Ranti Ibnu Adam, Riza Islami Pasha, Ramadhan Jamaludin, Asep Jaman, Jajam Haerul Lenteraningati, Anggun M Rayhan Rizqullah Syarif Maulana, Yuzril Nur Muhammad Fajar Estu Nugroho Nurul Abada, Oki Prihandani, Kamal Putra, Ikhwan Wiratama Ramadani, Daffa Tama Rika Yunita, Rika Rismawati, Imas Riza Ibnu Adam, Riza Ibnu Rizka, Alifa Maha Rizkika, Putri Rizky Fawzy, Ray Safaat, Ilham Sallamah, Afifah Nur Salsabila, Alifa Sanjaya, Nurlana Saputra, Reza Aditya savina, savina Setiawan, Fikri Maulana Sopiatul Ulum Sukma Nurmakarim, Hilmy Sunandar, Adi Tubagus, Ayu Shafira Wati, Sukma Winanto, Tawang Sahro