IJISTECH (International Journal Of Information System & Technology)
Vol 1, No 1 (2017): November

Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting)

Sandy Putra Siregar (STIKOM Tunas Bangsa Pematangsiantar)
Anjar Wanto (STIKOM Tunas Bangsa Pematangsiantar)



Article Info

Publish Date
13 Nov 2017

Abstract

Artificial Neural Networks are a computational paradigm formed based on the neural structure of intelligent organisms to gain better knowledge. Artificial neural networks are often used for various computing purposes. One of them is for prediction (forecasting) data. The type of artificial neural network that is often used for prediction is the artificial neural network backpropagation because the backpropagation algorithm is able to learn from previous data and recognize the data pattern. So from this pattern backpropagation able to analyze and predict what will happen in the future. In this study, the data to be predicted is Human Development Index data from 2011 to 2015. Data sourced from the Central Bureau of Statistics of North Sumatra. This research uses 5 architectural models: 3-8-1, 3-18-1, 3-28-1, 3-16-1 and 3-48-1. From the 5 models of this architecture, the best accuracy is obtained from the architectural model 3-48-1 with 100% accuracy rate, with the epoch of 5480 iterations and MSE 0.0006386600 with error level 0.001 to 0.05. Thus, backpropagation algorithm using 3-48-1 model is good enough when used for data prediction.

Copyrights © 2017






Journal Info

Abbrev

ijistech

Publisher

Subject

Computer Science & IT

Description

IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in the computer science and their applications in business, industry and other subjects. The computer science is a branch of engineering ...