Yuniarossy, Brescia Ayundina (2024) Implementasi Model IndoBERT Pada Analisis Sentimen Terhadap Isu Feminisme di Twitter. Undergraduate thesis, UPN Veteran Jawa Timur.
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (Cover)
Skripsi - Cover.pdf Download (1MB) |
|
Text (Bab I)
Skripsi - Bab 1.pdf Download (114kB) |
|
Text (Bab II)
Skripsi - Bab 2.pdf Restricted to Repository staff only until 28 July 2026. Download (346kB) |
|
Text (Bab III)
Skripsi - Bab 3.pdf Restricted to Repository staff only until 28 July 2026. Download (195kB) |
|
Text (Bab IV)
Skripsi - Bab 4.pdf Restricted to Repository staff only until 28 July 2026. Download (1MB) |
|
Text (Bab V)
Skripsi - Bab 5.pdf Download (98kB) |
|
Text (Daftar Pustaka)
Skripsi - Daftar Pustaka.pdf Download (166kB) |
|
Text (Lampiran)
Skripsi - Lampiran.pdf Restricted to Repository staff only Download (236kB) |
Abstract
This research focuses on analyzing public sentiment towards the issues of Domestic Violence and Sexual Harassment in Indonesia, two serious and far-reaching social issues. In the digital age, social media such as Twitter has become a platform for expressing public opinion. Using the IndoBERT model, a variant of the Indonesian language-specific Bidirectional Encoder Representations from Transformers (BERT) for public sentiment analysis on two social issues. This research shows that IndoBERT is able to classify public sentiment with 89% accuracy on the Sexual Harassment dataset without Bag of Words (BoW) and SMOTE feature extraction. The data used in this study was obtained through a crawling process from Twitter with a total of 3007 data from both topics. After that, a preprocessing stage is carried out to clean the data from noise. The sentiments of the collected tweets are labeled as positive, negative, and neutral. This research shows that IndoBERT is effective in classifying public sentiment and can help in understanding the public perception of feminism issues, especially domestic violence and sexual harassment.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||||||
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA76.6 Computer Programming |
||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||||||
| Depositing User: | Brescia Ayundina Yuniarossy | ||||||||||||
| Date Deposited: | 30 Jul 2024 04:01 | ||||||||||||
| Last Modified: | 30 Jul 2024 04:01 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/27959 |
Actions (login required)
 |
View Item |