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@article{JMASIF31450, author = {Sulistia Yulian and Suhartono Suhartono}, title = {Pengenalan Bahasa Isyarat Huruf Abjad Menggunakan Metode Learning Vector Quantization (LVQ)}, journal = {Jurnal Masyarakat Informatika}, volume = {8}, number = {1}, year = {2017}, keywords = {}, abstract = {Komunikasi paling efektif bagi mereka yang kurang beruntung (dalam hal ini penderita tuna rungu) adalah komunikasi non verbal. Komunikasi non verbal menggunakan gerakan tangan maupun gerakan tubuh dalam komunikasinya. Pada masyarakat umum masih sedikit yang mengerti bahasa isyarat, maka penelitian ini bertujuan mengimplementasikan aplikasi pengenalan bahasa isyarat huruf abjad secara komputasi menggunakan pengenalan pola. Jaringan syaraf tiruan Learning Vector Quantization (LVQ) dapat digunakan untuk melakukan klasifikasi sebuah pola berdasarkan permasalahan tertentu seperti halnya dalam pengenalan bahasa isyarat huruf abjad. Tahapan processing yang harus dilalui sebelum dilakukan pelatihan terhadap Jaringan syaraf tiruan Learning Vector Quantization (LVQ) adalah grayscalling, thresholding, cropping, dan scalling. Keluaran dari aplikasi ini berupa identifikasi huruf abjad “A”-“Z” berupa text, dimana text yang dihasilkan bersesuaian dengan huruf alfabet pada sistem isyarat bahasa Indonesia (SIBI). Hasil dari pengujian penelitian ini dapat mengenali 26 huruf isyarat, dengan tingkat akurasi sebesar 61,54%.}, issn = {2777-0648}, pages = {1--8} doi = {10.14710/jmasif.8.1.31450}, url = {https://ejournal.undip.ac.id/index.php/jmasif/article/view/31450} }
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