Monitoring public concern in the surrounding environment to certain events is done to address changes in public behavior individually and socially. The results of monitoring public attention can be used as a benchmark for related parties in making the right policies and strategies to deal with changes in public behavior as a result of the COVID-19 pandemic. Monitoring public attention can be done using Twitter social media data because the users of the media are quite high, so that they can represent the aspirations of the general public. However, Twitter data contains varied topics, so a classification process is required to obtain data related to COVID-19. Classification is done by using word embedding variations (Word2Vec and fastText) and deep learning variations (CNN, RNN, and LSTM) to get the classification results with the best accuracy. The percentage of COVID-19 data based on the best accuracy is calculated to determine how high the public's attention is to the COVID-19 pandemic. Experiments were carried out with three scenarios, which were differentiated by the number of data trains. The classification results with the best accuracy are obtained by the combination of fasText and LSTM which shows the highest accuracy of 97.86% and the lowest of 93.63%. The results of monitoring public attention to the time vulnerability between June and October show that the highest public attention to COVID-19 is in June.
| Published by | Ikatan Ahli Informatika Indonesia |
| Journal Name | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Contact Phone | +628126777956 |
| Contact Name | Yuhefizar |
| Contact Email | jurnal.resti@gmail.com |
| Location | , INDONESIA |
| Website | RESTI| http://jurnal.iaii.or.id/index.php/RESTI| |
| ISSN | ISSN : 25800760, EISSN : 25800760, DOI : https://doi.org/10.29207/resti.v2i3.606, |
| Core Subject | Science, Engineering, |
| Meta Subject | Computer Science & IT, Engineering, |
| Meta Desc | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan |
| Penulis | Alvi Hasanah, Novrindah , Nanik Suciati , Diana Purwitasari |
| Publisher Article | Ikatan Ahli Informatika Indonesia (IAII) |
| Subtitle Article | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021 |
| Scholar Google | http://scholar.google.com/scholar?q=%2Bintitle%3A&… |
| View Article | https://jurnal.iaii.or.id/inde… |
| DOI | https://doi.org/10.29207/resti.v5i1… |
| DOI Number | DOI: 10.29207/resti.v5i1.2927 |
| Download Article [1] | https://jurnal.iaii.or.id/index.php/REST… |
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