Money Authenticity Detector Design Using Artificial Neural Network Method for Blinds
Windarti Aji, Miftachul Ulum, Aslih Nur‘ Afifah · Journal of Physics Conference Series · 2020
Abstract Heretofore, there are still many people having difficulties to differ authenticity of paper money, especially for blind people. An individual is defined blind when he must use alternative technique to replace his visual function. In this case, a blind person may use his hearing or touching senses to read the demanded information. This research aims to create a device to find out authenticity of paper money with voice output. This device uses TCS3200 sensor and Led UV to detect the authenticity of paper money it gained red, green, and blue as the input process by using artificial neural network. This method would firstly undergo data training so it would have scores to classify the authenticity. The test of paper money used 1DR 1,000.00, IDR 2,000.00, IDR 5,000.00, IDR 10,000.00, IDR 20,000.00, IDR 50,000.00, and IDR 100,000.00 issued in 2000 until 2016 with 4 different test positions. Based on the trials, it gained successful level in detecting the authenticity by using the network as much as 100%.