Sentiment Analysis Tweet Pilkada 2020 Saat Pandemik COVID-19 di Media Sosial Twitter Menggunakan Metode 1D Convolutional Neural Network

Authors

  • Ganjar Tata Pangestu Universitas Ahmad Dahlan, Yogyakarta
  • Miftahurrahma Rosyda Universitas Ahmad Dahlan, Yogyakarta

DOI:

https://doi.org/10.30865/mib.v6i2.3765

Keywords:

Natural Language Processing, NLP, Sentiment Analysis, Python, 1D Convolutional Neural Network

Abstract

Pilkada 2020 is a debate since it takes place in the midst of the COVID-19 pandemic. The emergence of comments from several social media such as Twitter. There are various public opinions that agree that the Pilkada will still be held, there are also other public opinions that support the postponement of the Pilkada until the COVID-19 pandemic ends. These different opinions require Sentiment Analysis which aims to obtain or find out the general opinion of the 2020 Regional Head Election during the Coronavirus pandemic. A total of 200 data in the form of tweets which are divided into 2 data, namely 20% test data and 80% training data obtained by retrieving data from Twitter using the twint library, based on predetermined keywords. The resulting data set is classified into three classes namely positive, neutral, and negative. In this test or research, deep learning uses the Convolutional Neural Network classification, because it has been proven effective in the case of natural language processing and can get good results in grouping sentences. From this research, the accuracy result is 72.50% with the epoch used is 25 epoch. From the increase in epochs, there is an increase in accuracy of 7-12% from the previous epoch variations.

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Published

2022-04-25

Issue

Vol. 6 No. 2 (2022): April 2022

Section

Articles

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