Handwriting Vocal Character Pattern Recognition: Implementation of Artificial Neural Network Algorithm for Electronic Medical Record

Vita Permatasari, Andri Permana Wicaksono, Ahmad Fahriannur


Medical Record (MR) necessary to determine right treatment to patient. It contained medical history of patient and made communication of health team easier. Data written in MR must  be  clear  and  presentable.  The  objective  of  the  research  was  establishing  a  system  that recognize vocal character patterns  and  translate it into  text.  This is  a preliminary research  of advanced  electronic  medical  record  which  allowed  the  doctors  or  the  other  health team in recording, saving and processing the data of medical records through the natural gestures. The input system is “A, I, U, E, O” character in handwriting that was written on tablet pen, then it was  directly  brought  up  to  preprocessing  stage.  Then,  the  introduction  was  done  through the backpropagation of artificial neural network algorithm which had 625 inputs, 2 hidden layers and 5 outputs. The data of ‘A’, ‘I’, ‘U’, ‘E’, and ‘O’ in vocal learning in which each character consisted of 5 samples. The success of A, I, U,E,O introduction system was as much as 100%, 80%, 66%, 80%, 80%. The experimental result show validity of the proposed method.

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