@thesis{thesis,
		author={Alifa  Reysha and Kusuma  Dine Tiara and Luqman  Luqman},
		title ={PENGENALAN KARAKTER TULISAN TANGAN HURUF BALOK 
MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN 
BACKPROPAGATION},
		year={2022},
		url={http://156.67.221.169/5818/},
		abstract={Artificial neural networks have spread everywhere and are used in applications, 
one of which is the application of character shapes from hand applications. Various 
patterns on the character letters have various handwriting models made by the author. 
The problem that arises in the process of hand recognition is how an introduction can 
recognize various letters with size, thickness, shape, and slope between one author and 
another. One of the algorithms on an artificial neural network is backpropagation which 
has undergone several significant changes made by a neural network that is continuously 
leveled up to a certain level to be able to generalize. The test results of the block letter 
handwriting character recognition system from 10 tests only 1 letter that was not legible, 
namely the letter D. The test resulted in the lowest error of 0.066672. The results of the 
test are 90% this means that the level of accuracy between the test data and produces 
90% this means that the level of accuracy of the test accuracy between the test data and 
the training data yields 90%. The implementation of the Backpropagation Neural 
Network method with small epochs in carrying out something in a pattern can cause 
errors that occur during training. By applying the Backpropagation Neural Network 
method, you will get a higher success rate for training than new data}
		}