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

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

Zamzami, Elviawaty Muisa (Unknown)
Hayanti, Septi (Unknown)
Nababan, Erna Budhiarti (Unknown)

Article Info

Publish Date
31 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 %.

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Journal Info
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Website

Abbrev

kinetik

Publisher

Universitas Muhammadiyah Malang

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Description

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve ...