Layanan journal yang disediakan oleh Perpustakaan Universitas Gunadarma
| Judul Artikel | : | APLIKASI JARINGAN SYARAF TIRUAN UNTUK MENGENALI TULISAN TANGAN HURUF A, B, C, DAN D PADA JAWABAN SOAl PILIHAN GANDA |
|---|---|---|
| Judul Terbitan | : | JURNAL MATEMATIKA, SAINS, & TEKNOLOGI |
| ISSN | : | 1411-1934 |
| Bahasa | : | IND |
| Tempat Terbit | : | TANGERANG |
| Tahun | : | 0000 |
| Volume | : | Vol. 12 Issue 1 0000 |
| Penerbit | : | PUSAT KEILMUAN |
| Frekuensi Penerbitan | : | DUA KALI SETAHUN |
| Penulis | : | Dwi Astuti Aprijani ; Unggul Utan Sufandi |
| Abstraksi | : | Artificial Neural Network (ANN) can be applied to recognice pattem, particularly at the stage of data classification. This study used a multilayer perceptron backpropagation ANN, an unsupervised learning algorfthm, to recognize the pattern of uppercase handwrfting on the answer sheet of multiple-choice exams. The application of this network involves mapping a set of input against a reference set of outputs. In this research, ANN was trained using' 8000 handwritten uppercase characters (A, a, C, and 0) consisting of 6000 training data characters (1500 characters for each letter) and 2000 testing data characters (500 characters for each letter). The result showed that for the most optimal performance, the archftecture and network parameters were 10 neurons in hidden layer, leaming rate of 0.1 and 3000 fteration times. The accuracies of the result using the optimal network archftecture and parameters were 90.28% for training data and 87. 35% for testing data. |
| Kata Kunci | : | artificial neural network; backpropagation; handwrfting recognftion; leaming rate |
| Lokasi | : | Tangerang Selatan |
| Terakreditasi | : | belum |