Open AccessAnalysis of Backpropagation Algorithms in Predicting World Internet Users
Author(s) -
Sunil Setti,
Anjar Wanto,
Muhammad Syafiq,
Andriano Andriano,
Bil Klinton Sihotang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1255/1/012018
Subject(s) - the internet , backpropagation , computer science , artificial neural network , internetworking , government (linguistics) , christian ministry , algorithm , world wide web , machine learning , linguistics , philosophy , theology
The internet is now a primary need for its users. According to the e-Marketer market research institute, there are the top 25 countries with the most internet users in the world. Indonesia is in the sixth position with a total of 112.6 million internet users. With the increasing number of internet users, it is expected to be able to contribute to advancing the economy and education in a country. To be able to increase the number of internet users, especially in Indonesia, it is necessary to predict in the coming years so that the government can provide adequate facilities and infrastructure in order to compensate for the growing number of internet users and as a precaution when there is a decrease in the number of internet users. The data used in this study focus on the data on the number of internet users in 25 countries in 2013-2017 sourced from the Indonesian Ministry of Communication and Information. The algorithm used is the Backpropagation Neural Network. Data analysis was performed using Artificial Neural Network method using Matlab R2011b. This study uses 5 architectural models. The best network architecture produced is 3-50-1 with an accuracy rate of 92% and the Mean Squared Error (MSE) value is 0.00151674.