Analysis of Community Sentiment on Twitter towards COVID-19 Vaccine Booster Using Ensemble Stacking Methods
SYIFA KHAIRUNNISA SALSABILA
Informasi Umum
Kode
23.04.1035
Klasifikasi
006.35 - Natural Language Processing, Computer Science
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Natural Language Processing, Analysis,
Dilihat
258 kali
Informasi Lainnya
Abstraksi
<p>The outbreak of the COVID-19 virus in Indonesia has not ended until the government has made various efforts to reduce this outbreak, such as the Large-Scale Social Restriction (PSBB) policy and the obligation of the entire community to vaccinate against COVID-19. The government has made a new policy for the community: booster vaccination for people who have already been vaccinated against COVID-19 1 and vaccinated against COVID-19 2. With this new policy, many people have given opinions on social media. One of them is Twitter social media. Positive and negative opinions given by Twitter users can be used as a source of information data. Because of these problems, researchers conducted a sentiment analysis of the booster vaccine using the Ensemble Stacking method. The dataset that has collected as many as 6,500 data from Twitter will be grouped into positive and negative class sentiments. The best results from this study using ensemble stacking and oversampling have an accuracy value of 80%.</p>
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Koleksi & Sirkulasi
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Pengarang
| Nama | SYIFA KHAIRUNNISA SALSABILA |
| Jenis | Perorangan |
| Penyunting | Jondrin, Widi Astuti |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2023 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
