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Vol. 6, No. 2, May 2021

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Diagonal Based Feature Extraction and Backpropagation Neural Network in Handwritten Batak Toba Characters Recognition

https://doi.org/10.22219/kinetik.v6i2.1212
Elviawaty Muisa Zamzami
Universitas Sumatera Utara
Septi Hayanti
Universitas Sumatera Utara
Erna Budhiarti Nababan
Universitas Sumatera Utara

Corresponding Author(s) : Elviawaty Muisa Zamzami

elvi_zamzami@usu.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 6, No. 2, May 2021

Abstract

Handwritten character recognition is considered a complex problem since one’s handwritten character has its characteristics.  Data used for this research was a photo of handwritten or scanned handwritten.  In this research, Backpropagation Neural Network (BPNN) was used to recognize handwritten Batak Toba character, wherein preprocessing stage feature extraction was done using Diagonal Based Feature Extraction (DBFE) to obtain feature value.  Furthermore, the feature value will be used as an input to BPNN. The total number of data used was190 data, where 114 data was used for the training process and another 76 data was used for testing. From the testing process carried out, the accuracy obtained was 87,19 %.

Keywords

Character Recognition Feature Extraction Backpropagation Neural Network Diagonal Based Feature Extraction
Zamzami, E. M., Hayanti, S., & Nababan, E. B. (2021). Diagonal Based Feature Extraction and Backpropagation Neural Network in Handwritten Batak Toba Characters Recognition. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 6(2). https://doi.org/10.22219/kinetik.v6i2.1212
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