ANALISIS DAN PERANCANGAN JARINGAN SARAF TIRUAN DENGAN METODE BACKPROPAGATION PADA APLIKASI PENGENALAN TANDA TANGAN
ABSTRACT: Artificial neural
network (ANN) with
backpropagation method is
part of a
multilayered feedforward neural
network (MFN) which has been developed to solve the problem approximation and
pattern classification. Application of ANN in pattern recognition is one of the
signature pattern recognition. Signature of each person are generally identical
but not the same. Often a person 's signature changes
every time. This
change concerns the
position, size and
pressure factors signature. Signature
is the most
widely used form
of identification of
a person. In
general, to identify the
signature is still done manually, by matching signatures at the time of the
transaction with a valid signature. Therefore, we need a system that can
analyze the characteristic signature making
it easier to
identify the person's
signature. The research
methodology used in the
development of the
system is a
method Rappid Guidelines
for Application Engineering (GRAPPLE). This
signature recognition process
through several stages.
First image through image processing stages, where the
image will be used as the image of the grayscaling. Once the image is converted into binary data by
using thresholding. Binary data obtained will be the input value to the
training process by using the backpropagation method. The results of the
training will be used for the process of signature recognition.
Penulis: Wilis Kaswidjanti,
Fani Widiastuti, Heru Cahya Rustamaji
Kode Jurnal: jptmesindd130314
