A signature is a marker or identity in a document. Signatures have an essential role in verifying and legalizing documents. The signature is not just any sign but is a legal one and is the original image of the owner. With the development of today's technology, signature pattern identification can not only be done manually but can also be done with the help of a computer. However, computers cannot immediately carry out the identification process, instead, a pattern recognition process is needed beforehand which can be done by extracting signature features. This research aims to determine signature ownership, so identification is required. Identification of signature patterns is needed to recognize and distinguish the signatures of each individual based on the characteristics of the signature. Therefore this research is expected to be an alternative to minimize signature recognition errors using the CNN (convolutional neural network) method. then taken with a scanner. The results of this research are that the Convolutional Neural Network method can recognize each signature image with an accuracy of 100% in the validation testing process and 85% in the testing process.
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