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@article{JMASIF31467, author = {Angga Saputra and Sukmawati Endah}, title = {Aplikasi Pengenalan Aksara Jepang Katakana Menggunakan Jaringan Syaraf Tiruan Learning Vector Quantization (LVQ)}, journal = {JURNAL MASYARAKAT INFORMATIKA}, volume = {7}, number = {2}, year = {2017}, keywords = {}, abstract = {Aksara Jepang katakana digunakan pada saat menuliskan kata-kata selain bahasa Jepang, misalnya nama orang asing dan kata-kata serapan dari bahasa asing. Bagi orang-orang yang sedang belajar aksara Jepang katakana, terkadang mengalami kesulitan dalam menghafalkannya, sehingga dibuat sebuah aplikasi pengenalan aksara Jepang katakana. Aplikasi ini dikembangkan menggunakan jaringan syaraf tiruan learning vector quantization. Tahapan yang dimiliki oleh aplikasi ini yaitu melakukan pre-processing pada citra aksara, mengekstrak fitur citra menggunakan transformasi wavelet diskrit, menyimpan data vektor citra, melakukan pelatihan data, dan melakukan pengenalan terhadap citra yang dimasukkan. Data pelatihan yang digunakan dalam aplikasi ini sebanyak 360 data tulisan tangan aksara katakana yang berasal dari 8 orang. Selanjutnya data-data ini akan terbagi menjadi 8 subset pada pengujian validitas menggunakan k-fold cross validation untuk mendapatkan nilai akurasi. Nilai akurasi pengenalan aksara terbaik hanya sebesar 47,50% dengan parameter α = 0.08 dan 0.09 dan epoch = 10.}, issn = {2777-0648}, pages = {7--13} doi = {10.14710/jmasif.7.2.31467}, url = {https://ejournal.undip.ac.id/index.php/jmasif/article/view/31467} }
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