Jurnal Matematika Sains dan Teknologi
Vol. 12 No. 1 (2011)

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)

Dwi Astuti Aprijani (Universitas Terbuka)
Unggul Utan Sufandi (Universitas Terbuka)

Article Info

Publish Date
15 Aug 2011

Abstract

Artificial Neural Network (ANN) can be applied to recognice pattern, particularly at the stage of data classification. This study used a multilayer perceptron 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 against a reference set of outputs. In this research, ANN was trained using 8000 handwritten uppercase characters (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 parameters were 10 neurons in hidden layer, learning rate of 0.1 and 3000 iteration times. The accuracies of the result using the optimal network architecture and parameters were 90.28% for training data and 87.35% for testing data.

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Journal Info
Jurnal Matematika Sains dan Teknologi
Website

Abbrev

JMST

Publisher

Universitas Terbuka

Subject

Agriculture, Biological Sciences & Forestry Mathematics Other

Description

Merupakan media informasi dan komunikasi para praktisi, peneliti, dan akademisi yang berkecimpung dan menaruh minat serta perhatian pada pengembangan Matematika, ilmu pengetahuan dan teknologi. Diterbitkan oleh Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas ...