Predicting News Article Popularity with Multi Layer Perceptron Algorithm

Authors

  • Arie Rachmad Syulistyo State Polytechnic Of Malang
  • Vira Meliana Agustin State Polytechnic Of Malang
  • Dwi Puspitasari State Polytechnic Of Malang

DOI:

https://doi.org/10.33633/jais.v7i2.6826

Abstract

Nowadays, news media seems to have been digitized. One of them is printed news which has now turned into online news. The increasing use of social media has made people interested in reading news online. News needs to attract readers with their headlines. Various online news media businesses want to know the future demand of readers, as well as whether the released news can reach more readers so that the news becomes popular. Therefore, with the increasing interest in online news today, this paper will analyze the performance of the Neural Network Algorithm and other artificial intelligence techniques in predicting the popularity of news articles that can help the media to know whether their news will become popular. The news article popularity prediction system can increase its revenue if there are advertisements in the news. The test results show that the accuracy of the Multi Layer Perceptron is 76% and Random Forest gives an accuracy of 70%.

Author Biography

Arie Rachmad Syulistyo, State Polytechnic Of Malang

information technology department

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Published

2022-09-07

Issue

Vol. 7 No. 2 (2022): Journal of Applied Intelligent System

Section

Articles

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