IDENTIFIKASI KEPRIBADIAN BERDASARKAN TANDA TANGAN MENGGUNAKAN BACKPROPAGATION NEURAL NETWORK (BPNN) - Kevin Andryani; Tony Tony; Sidik Mulyono (Jurnal Ilmu Komputer dan Sistem Informasi, 2016)
From the beginning until now, people try to get to know him. That is why people try to develop methods to identify themselves, and one of them is graphology. In Graphology, handwriting is  analyzed in order to obtain information about the personality of the author. Development of image processing and pattern recognition led to the introduction of the signature can be identified automatically by using neural networks. One of the development is the creation of applications based signature identification personality using Backpropagation Neural Network (BPNN). First step is doing feature extraction on the image of the signature with the method of Principal Component Analysis (PCA), the training stage made to the image that dimensions has been reduced to obtain optimal weights connectedness with BPNN. Tests performed on image data that has been trained and not trained previously. The results of personality identification is in the form of brain dominance and learning modalities from the signature.