Aplikasi Jaringan Syaraf Tiruan untuk Mengenali Tulisan Tangan Huruf A, B, C, dan D pada Jawaban Soal Pilihan Ganda (Studi Eksplorasi Pengembangan Pengolahan Lembar Jawaban Ujian Soal Pilihan Ganda di Universitas Terbuka)  

Oleh:

Aprijani, Dwi Astuti

Jenis: Article from Journal - ilmiah nasional
Dalam koleksi: Jurnal Matematika, Sains, dan Teknologi vol. 12 no. 1 (Mar. 2011), page 11-17.
Topik: Artificial Neural Network; Backpropagation; Handwriting Recognition; Learning Rate

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: JJ138.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Artificial Neural Network (ANN) can be applied to recognice pattern, particulary at the stage of data classiffication. This study used a multilayer perception backpropagation ANN, an unsupervised learning algorithm, to recognize the pattern of uppercase handwriting on the answer sheet of multiple-choice exams. The application of this network involves mapping a set of input agains a reference set of outputs. In this research, ANN was trained using 8000 handwritten uppercase character (A,B,C, and D) 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 architecture and network paarmeters were 10 neurons in hidden layer, learning rate of 0.1 and 300 iteration times. The accucies of the result using the optimal network architecture were 90.28% for training data and 87.35% for testing data.

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