Deep learning application using neural network classification for cyberspace dataset with backpropagation algorithm and log-linear models

Authors

  • Baiq Siska Febriani Astuti Institut Teknologi Sepuluh Nopember
  • Tuti Purwaningsih Universitas Islam Indonesia

Abstract

This study aims to classify bloggers in the Kohkiloye and Boyer Ahmad Province in Iran where causes of users tend cyberspace on there. The database was got from UCI Machine Learning Repository. There are 100th object and 6th variables. All of the variables were Professional Bloggers, Political and Social Space (LPSS), Local Media Turnover (LMT), Political Caprice, Topics, and Degree. This study has using Artificial Neural Network with backpropagation algorithm and Log-linear models for classify Bloggers (Cyber Space). We classify blogger to two groups: professional bloggers and seasonal (temporary) bloggers. The result of this study is Neural network with backpropagation algorithm has been shown to be useful tool for prediction, especially for this case. From this study, we can see on the result that miss-classification with backpropagation algorithm less than using Log-Linear Models

Author Biography

Tuti Purwaningsih, Universitas Islam Indonesia

Statistics Department

References

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Published

2018-01-14

Issue

Vol. 12 No. 1: January 2018

Section

Articles

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