MARTBOARD-BASED INDONESIAN SIGN LANGUAGE (BISINDO) DEEP LEARNING MODEL FOR DEAF STUDENTS AT SLB PEMBINA MEDAN
DOI:
https://doi.org/10.46244/visipena.v17i1.3573Keywords:
Deep Learning, Bisindo, Smartboard, deaf students, learning modelsAbstract
Deaf students in Indonesian special schools (SLB) face persistent barriers in accessing interactive instructional media that align with their visual-spatial cognitive needs and Bisindo linguistic identity. While prior studies have explored sign language recognition technologies and general deep learning algorithms, a critical gap remains in integrating pedagogical deep learning principles with disability-specific interactive media within special education classrooms. This study aimed to develop and validate a Smartboard-based Indonesian Sign Language (Bisindo) deep learning instructional model for deaf students at SLB Pembina Medan. Employing a Research and Development (R&D) approach following the Borg and Gall ten-step model, the study involved needs analysis, product development, expert validation, and field testing. Validation instruments were assessed for content validity using the Content Validity Index (CVI) and Content Validity Ratio (CVR), and reliability was established through inter-rater agreement. The product was evaluated by one learning expert, one Bisindo expert, and one media expert, followed by small-group trials (N = 3 teachers) and large-group trials (N = 3 teachers). Ethical approval was obtained from the institutional review board prior to data collection. Results demonstrated exceptional feasibility: material experts rated the product at 97.06%, Bisindo experts at 95.59%, and media experts at 91.67%, all classified as "very feasible." Small-group teacher trials yielded 88.33% (feasible), while large-group trials achieved 96.66% (very feasible). The developed model offers a replicable pedagogical framework that integrates Bisindo linguistic features, deep learning pedagogy, and Smartboard interactivity, contributing to inclusive digital learning practices for deaf students in special education contexts.
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Aka, K. A. (2019). Integration Borg & Gall (1983) and Lee & Owen (2004) models as an alternative model of design-based research of interactive multimedia in elementary school. In Journal of Physics: Conference Series (Vol. 1318, Issue 1, p. 12022). https://doi.org/10.1088/1742-6596/1318/1/012022
Al Fuad, Z., Helminsyah, & Musdiani. (2023). Pengembangan Modul Ajar Tematik SD Berbasis Digital Di Provinsi Aceh. Jurnal Visipena, 14(2), 85–97. https://doi.org/10.46244/visipena.v14i2.2351
Aljabar, A., & Suharjito. (2020). BISINDO (Bahasa Isyarat Indonesia) sign language recognition using CNN and LSTM. Advances in Science, Technology and Engineering Systems Journal, 5(5), 282–287. https://doi.org/10.25046/aj050535
Altarika, E., & Sari, W. P. (2023). Pengembangan Deteksi Realtime untuk Bahasa Isyarat Indonesia dengan Menggunakan Metode Deep Learning Long Short Term Memory dan Convolutional Neural Network. Jurnal Teknologi Informatika Dan Komputer, 9(1), 1–3. https://doi.org/10.30649/jtik.v9i1.33
Andrayani, R. L. M. (2024). Ethics and integrity in early childhood education research: A case study of digital media use in inclusive schools. In Proceedings of the International Conference on Education and Technology (pp. 208–215). https://doi.org/10.2991/978-94-6463-429-7_28
Borg, W. R. (1983). Educational research: An introduction (4th (ed.)). Longman.
Firman, F., & Mirnawati, M. (2023). How to develop scientific writing techniques teaching materials with the development of the Borg & Gall model. In AIP Conference Proceedings (Vol. 2805, Issue 1, p. 20044). https://doi.org/10.1063/5.0157206
Haqqi, H., & Wijayati, H. (2019). Revolusi industri 4.0 di tengah society 5.0: sebuah integrasi ruang, terobosan teknologi, dan transformasi kehidupan di era disruptif. Anak Hebat Indonesia.
Israldi, T. (2022). Klasifikasi American Sign Language Menggunakan Convolutional Neural Network. Klasifikasi American Sign Language Menggunakan Convolutional Neural Network, 4(3), 1376–1385. https://doi.org/10.1234/kaslmcnn.v4i3.456
Kasmini, L. (2023). Pengembangan Media Video Animasi Berbasis Kearifan Lokal Untuk Meningkatkan Literasi Lingkungan Pada Pembelajaran IPA. Jurnal Visipena, 14(2), 68–84. https://doi.org/10.46244/visipena.v14i2.2340
Kautsar, I., Borman, R. I., & Sulistyawati, A. (2019). Aplikasi pembelajaran bahasa isyarat bagi penyandang tuna rungu berbasis android dengan metode Bisindo. Semnasteknomedia Online, 3(1), 4–9. https://doi.org/10.33020/semnasteknomedia.v3i1.112
Liu, Z. L. (2025). Deep learning. In Artificial intelligence for engineers: Basics and implementations (pp. 191–220). Springer. https://doi.org/10.1007/978-3-031-35135-9_7
Malathi, P., Gayathri, B. S., Lakshmi, S. G., Sahitya, E., & Rupa, J. S. (2023). Virtual Handwriting Based Smart Board Using Deep Learning. In 2023 Innovations in Power and Advanced Computing Technologies (i-PACT) (pp. 1–7). IEEE. https://doi.org/10.1109/i-PACT57855.2023.10420992
Muvid, M. B. (2024). Menelaah wacana kurikulum deep learning: Urgensi dan peranannya dalam menyiapkan generasi emas Indonesia. Jurnal Edu Aksara, 3(2), 80–93. https://doi.org/10.61100/eduaksara.v3i2.73
Namiri, Z., Patimah, S., Subandi, S., & Makbulloh, D. (2023). Optimalisasi penggunaan teknologi digital dalam pembelajaran di SMP IT Ar Raihan Bandar Lampung. At-Tajdid: Jurnal Pendidikan Dan Pemikiran Islam, 7(2), 465–474. https://doi.org/10.24014/atjpi.v7i2.17892
Putri, T., Mandasari, N., & Maharani, T. (2024). Pengaruh model pembelajaran problem based learning (PBL) berbantuan smart board terhadap hasil belajar matematika siswa kelas III SD Negeri 17 Kota Lubuklinggau. Linggau Journal of Elementary School Education, 4(1), 228–244. https://doi.org/10.61100/ljese.v4i1.89
Ragoonaden, K. (2015). Mindful education and well-being. In Mindful teaching and learning: Developing a pedagogy of well-being (pp. 17–32). Lexington Books.
Rahim, B. (2023). Media pendidikan. PT. RajaGrafindo Persada-Rajawali Pers.
Reddy, B. K., & Rohit, V. B. (2023). Real-Time Interactive Virtual Smart Board Using Artificial Intelligence. In International Conference on Human-Centric Smart Computing (pp. 417–427). Springer. https://doi.org/10.1007/978-981-99-4755-3_38
Rosenstock, I. M. (1974). The health belief model and preventive health behavior. Health Education Monographs, 2(4), 354–386. https://doi.org/10.1177/109019817400200405
Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the health belief model. Health Education Quarterly, 15(2), 175–183. https://doi.org/10.1177/109019818801500203
Solo, L., Lustyantie, N., & Murtadho, F. (2025). Developing An English-Speaking Skills Assessment Rubric For Autism Children Using Universal Design For Learning. Jurnal Visipena, 16(1), 48–58.
Soon, V. K. L., & Rusdin, N. M. (2024). ICT use among special education teachers in teaching hearing-impaired students: A systematic literature review. Journal of Electrical Systems, 20(10s), 8017–8028. https://doi.org/10.52783/jes.4448
StatPearls. (2024). The health belief model of behavior change. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK606120/
Ulfah, S. M., & Ubaidah, S. (2023). Penerapan bahasa isyarat dalam pembelajaran bagi anak berkebutuhan khusus tuna rungu. Journal of Dissability Studies and Research (JDSR), 2(1), 29–43. https://doi.org/10.61100/jdsr.v2i1.34
Wu, T., & Li, Y. (2025). A systematic review of the utility of assistive technologies for SEND students in schools. Frontiers in Education, 10, 1523797. https://doi.org/10.3389/feduc.2025.1523797
Xu, Y., Li, Y., Shaw, N., Tsai, C. H., & Zhang, H. (2024). 1DCNNTrans: BISINDO sign language interpreters in improving the inclusiveness of public services. ArXiv Preprint ArXiv:2409.01975. https://doi.org/10.48550/arXiv.2409.01975
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