PENGENALAN KARAKTER PADA SURAT MASUK MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION
DOI:
https://doi.org/10.26418/justin.v1i1.923Keywords:
Character recognition, neural network, backpropagation, pattern recognition, optical character recognitionAbstract
A letter is a means of communication
to convey information in writing by one party to
the other party. It functions include five things:
means notices, requests, thoughts and ideas. A
formal letter is a letter that contain the official
or a particular business problem. Along with the
increasing demand for the current document
digitalization, OCR (Optical Character
Recognition) application is often used to
identify the image of characters then will be
converted into text files. Furthermore, Artificial
Neural Network is one kind of technology
approach that promising can increase the
computer's ability to recognize and represent
pattern. Meanwhile, Backpropagation is one
kind of neural network algorithm which
common used. Therefore, a character
recognition application using neural network
backpropagation will be designed. Application
need a data image of document letter as an
input, it"™s obtained from scanning, then
continued by pre-processing, segmentation,
normalization size process. After all, it"™s ready
to be processed in network and will get
characters text as an output. Result of the test
had been showed that, the best recognition
accuracy rate on the characters trained, font
Arial, with learning rate (α) 0.2, momentum ( µ)
0.5 and 15 epoch is 71.95% and for the
characters without trained, font Times New
Roman and Courier New, the recognition
accuracy rate is 40.24%. Overall, the result of
percentage success the recognition of 790
characters in 15 document letter is 84.56%.
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Siang, J.J. (2005). Jaringan Saraf Tiruan dan Pemrogramannya Menggunakan Matlab. Yogyakarta : Penerbit ANDI.
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