E3S Web Conf.
Volume 328, 2021International Conference on Science and Technology (ICST 2021)
|Number of page(s)||4|
|Section||Information System, Big Data, Design Application, IOT|
|Published online||06 December 2021|
Implementation of Backpropagation Artificial Network Methods for Early Children’s Intelligence Prediction
Informatics Department, Faculty of Engineering, Universitas Khairun, Ternate, Indonesia
* Corresponding author: firstname.lastname@example.org
Intelligence is the ability to process certain types of information derived from human biological and psychological factors. This study aims to implement a Backpropagation artificial neural network for prediction of early childhood intelligence and how to calculate system accuracy on children's intelligence using the backpropagation artificial neural network method. The Backpropagation Neural Network method is one of the best methods in dealing with the problem of recognizing complex patterns. Backpropagation Neural Networks have advantages because the learning is done repeatedly so that it can create a system that is resistant to damage and consistently works well. The application of the Backpropagation Neural Network method is able to predict the intelligence of early childhood. The results of the calculation of the Backpropagation Artificial Neural Network method from 42 children's intelligence data being tested, with 27 training data and 15 test data, the results obtained 100% accuracy percentage results.
Key words: Artificial Network / Algoritm / Early childhood intelligence
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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