Identifikasi Pola Tanda Tangan Berbasis Jaringan Syaraf Tiruan Dengan Metode Learning Vector Quantization - Yoannes Romando Sipayung; Suamanda Ika Novichasari (Universitas Ngudi Waluyo, 2018)
Abstrak - The introduction of signature patterns is one of the fields of pattern recognition that is currently developing. Each person's signature is generally identical but not the same. LVQ is a method of artificial neural networks to conduct learning in a supervised competitive layer. There are previous studies that use this method, but in these studies do not include the processing time needed to identify signature patterns. This research will test using this method. In this study, used image data with a size of 433 x 276 pixels as many as 300 pieces from 30 people, where each person was taken 10 signatures. For training data, the data is 180 signatures, while 120 test data are used for the test data. This study uses Canny edge detection to obtain an edge in the signature image. During the training process and LVQ testing, the process was carried out 3 times. The results of the training and testing with the LVQ metodel indicate that the method can identify the signature pattern well.Â Keywords:Â Signature Patterns, Artificial Neural Network, Learning Vector QuantizationÂ