BibTex Citation Data :
@article{JMASIF34870, author = {Afifatul Mukaroh and Priyo Sasongko}, title = {Sistem Pengenalan Nomor Pelat Kendaraan Menggunakan Jaringan Syaraf Tiruan Backpropagation}, journal = {JURNAL MASYARAKAT INFORMATIKA}, volume = {11}, number = {2}, year = {2020}, keywords = {Pengenalan Karakter, Nomor Pelat Kendaraan, Jaringan Syaraf Tiruan, Backpropagation}, abstract = {Dalam pengawasan lalu lintas, pengenalan nomor pelat kendaraan menjadi penting untuk dilakukan. Hal ini dikarenakan pengenalan nomor pelat kendaraan memiliki banyak tujuan seperti identifikasi kendaraan curian, identifikasi kendaraan yang melanggar tata tertib, manajemen perparkiran, pengecekan keluar masuk kendaraan, dan lain sebagainya. Sayangnya jumlah kendaraan yang semakin tinggi membuat hal ini tidak bisa lagi dilakukan secara manual. Maka dari itu dibutuhkan sebuah machine vision yang dapat mengenali nomor pelat kendaraan dengan cepat dan akurasi yang tinggi. Pada penelitian ini dikembangkan sistem pengenalan nomor pelat kendaraan menggunakan jaringan syaraf tiruan backpropagation (JST BP). Sistem ini mencari model terbaik JST BP yang mampu melakukan pengenalan karakter-karakter pada pelat dengan waktu tercepat namun dengan akurasi yang tetap tinggi. Dari model terbaik yang didapatkan, sistem pengenalan nomor pelat kendaraan ini memiliki persentase keberhasilan sebesar 99.80% pada data pelat yang digunakan sebagai pembentuk model dan sebesar 96.10% pada data verifikasi.}, issn = {2777-0648}, pages = {27--35} doi = {10.14710/jmasif.11.2.34870}, url = {https://ejournal.undip.ac.id/index.php/jmasif/article/view/34870} }
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