Penerapan Algoritma Artificial Neural Network untuk Klasifikasi Opini Publik Terhadap Covid-19

Euis Saraswati; Yuyun Umaidah; Apriade Voutama

doi:10.29407/gj.v5i2.16125

Authors

Euis Saraswati Universitas Singaperbangsa Karawang
Yuyun Umaidah Universitas Singaperbangsa Karawang
Apriade Voutama Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.29407/gj.v5i2.16125

Keywords:

Covid-19, Public Opinion, Artificial Neural Network, Text Mining

Abstract

Coronavirus disease (Covid-19) or commonly called coronavirus. This virus spreads very quickly and even almost infects the whole world, including Indonesia. A large number of cases and the rapid spread of this virus make people worry and even fear the increasing spread of the Covid-19 virus. Information about this virus has also been spread on various social media, one of which is Twitter. Various public opinions regarding the Covid-19 virus are also widely expressed on Twitter. Opinions on a tweet contain positive or negative sentiments. Sentiments of sentiment contained in a tweet can be used as material for consideration and evaluation for the government in dealing with the Covid-19 virus. Based on these problems, a sentiment analysis classification is needed to find out public opinion on the Covid-19 virus. This research uses Artificial Neural Network (ANN) algorithm with the Backpropagation method. The results of this test get 88.62% accuracy, 91.5% precision, and 95.73% recall. The results obtained show that the ANN model is quite good for classifying text mining.

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