PENGGUNAAN JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA MODEL PERBANDINGAN KESAMAAN TANDA TANGAN

Aidi Adri, . (2013) PENGGUNAAN JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA MODEL PERBANDINGAN KESAMAAN TANDA TANGAN. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Signature is a handwriting or curved object of someone to mark document or absenteeism. The signature of each people are changing every time. Those changing are concern about position, size and the hand pressure. In the new era like now, the signature can be doing with two media which are manually and with digital device. On this writing is application model developed for knowing the comparison level of two signature image has taken by manually and with android smartphone version 4.0 Ice Cream Sandwich. The taking digital image by android smartphone can be done by using android smartphone application which is name Digital Signature Creator. Without cropping process. Then retrieval of digital image data do physically in A4 paper using spidol. After that it scan and then do cropping process. After that do change the size are resolution of the image. So the image data to be processed is not too big to get the value traits. To this traits through several steps to change the original image to gray image or gray scale then do sharpening image. After get sharpening image result then do edge detection process by using canny method to get characteristic of the image from android smartphone or manually. This writing are using two backpropagation artificial neural network to get the comparing result. In JST A is getting percentage different that is 60% proportionate 70% and by testing to the result of JST B getting comparing percentage same which is 70 %.

Item Type:	Thesis (Skripsi)
Additional Information:	[No. Panggil : 0910511049] [Pembimbing) : Jayanta] [Penguji Lembaga : Bambang Tri Wahyono] [Penguji Ahli : Didit Widiyanto]
Uncontrolled Keywords:	Comparing, Signature, Android Smartphone, Gray scale Image, Image Sharpening, Edge Detection, Artificial Neural Network, Back-propagation
Subjects:	Q Science > Q Science (General)
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Muamar Khadafi
Date Deposited:	27 Jun 2024 06:33
Last Modified:	27 Jun 2024 06:33
URI:	http://repository.upnvj.ac.id/id/eprint/30332

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