In the recent years, automated systems have become an integral part of daily tasks that only a human can do before. Automated systems are meant to help human to do task that involves knowledge, reasoning and experience. The integral part of an automated system is artificial intelligence and one of the application of artificial intelligence in automated system is Optical Character Recognition (OCR). OCR let a computer recognize character through visual interpretation and recognize character automatically without help from human. There are several algorithms that we can use to create OCR system, such as template matching, support vector machine (SVM), hidden markov model, hausdorff distance and artificial neural network. Artificial neural network is the most popular algorithm that has been used by researcher to solve pattern recognition problems1 . Artificial neural network can be used to solve many problems and it can be trained over time to gain its knowledge or to enhance its accuracy in recognizing patterns. Artificial neural network is an abstraction of biological neural network that simulate the way it works in biological brain. Neurons are interconnected by synapsis that carries information and it can be modified by training process. There are several training processes that can be used to train artificial neural network, one of them is backpropagation training method. Backpropagation training method involves feedforward of the input training pattern, calculation and backpropagation of error, and adjustment of the weights in synapses.