Analysis of Pattern Recognition of Disorders in Children Using Artificial Neural Network (ANN) and Decision Tree Methods: A Case Study of Disorders in Children with Disabilities

Abstract

In this era of globalization, technological developments in the field of digital information have greatly affected services in the health sector in healing and meeting public satisfaction. Digital technology-based services are needed by children with disabilities so that they can be given superior and effective treatment. Digital technology services are used as a clustering and pattern recognition system using Artificial Neural Network (ANN) and decision tree. The data collection process is done by taking a video of a child walking on a track in the form of manila cardboard whose feet have been colored with food coloring so that the footprints can be seen clearly. After that, Artificial Neural Network (ANN) and decision tree have two stages, namely the training stage and the testing stage. The training stage is carried out using 20 respondent data from children who walk. The testing stage is carried out using three new data that are different from the training stage. From these two methods, a high accuracy rate of 99.91% is obtained for ANN and close to 100% for decision trees.