Ekstraksi Ciri Batang untuk Pengenalan Nomer Rekening Tulisan Tangan dengan Jaringan Syaraf Tiruan Perambatan Balik
Abstract: Handwriting number
recognition was being challenge problem to do in the recent years. The main
objective for our research waso recognized handwritten account number. The
original data was bank deposit slip that acquired by scanner. Before do the
recognition of account number handwritten, first step that must be done was
located account number on the bank deposit slip. After the location was found
then the account number was segmented to cut up each numbern. After cutting the
stem then performed feature extraction to obtain a vector which was fed to the
neural network system for recognition rate. System back propagation neural
network for handwritten digit pattern recognition was designed by 168neuron
consists of input layer, 70 neurons in the hidden layer and 10 neurons in the
output layer. The results obtained in this study were 83.78% of the data slip
can be recognized correctly.
Penulis: Farida Asriani, Azis
Wisnu Widhi Nugraha
Kode Jurnal: jptindustridd120174