Implementation of Signature Recognitionby Using Backpropagation

Sovia, Rini and Yanto, Musli and Nursanty, Widya (2016) Implementation of Signature Recognitionby Using Backpropagation. Journal of Computer Science and Information Technology, 1 (1). pp. 30-44.


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Many things are required by all parties, especially in the process of recognition of one's identity, ranging from health care, maintenance of bank accounts, aviation services, immigration and others.Many ways of proving one's identity and the most popular one is using a signature.The signature is used as an identification system which serves to recognize a person's identity.Recognition process is still done manually by matching the signature by the person concerned.Therefore, the very need for a system that is able to analyze and identify the characteristics of the signature, so it can be used as an alternative to simplify the process of introducing people’s signature.Artificial neural networks can be used as one of the solutions in identification of signatures.Artificial neural network is a branch of science of artificial intelligence that is capable of processing information with the performance of certain characteristics.Artificial neural networks have some method such as perceptron, Hopfield discrete, Adaline, Backpropagation, and Kohonen.In this paper, the artificial neural network with back propagation method is applied in the process of signature and pattern recognition which provided a solution that is able to analyze and recognize people's signature.Implementation of the application of neural networks in pattern recognition signature can further be applied to any computer that handles problems in the process of matching one's data. Keywords: Neural network;Backpropagation; Identification; Signature.

Item Type: Article
Subjects: 0 Research > Ilmu Komputer > Sistem Informasi
0 Research > Ilmu Komputer > Teknologi Komputer
Divisions/ Fakultas/ Prodi: LPPM (Lembaga Penelitian dan Pengabdian Masyarakat) UPI "YPTK"
Depositing User: Administrator
Date Deposited: 13 Mar 2018 07:35
Last Modified: 13 Mar 2018 07:35

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