Muludi, Kurnia and Shofiana, Dewi Asiah and Anesca, Ni Putu Ayu (2021) Sentiment Analysis Protokol Kesehatan Virus Corona Dari Tweet Menggunakan Word2Vec Model dan Recurrent Neural Network Learning. Jurnal Pepadun, 2 (3). pp. 432-439. ISSN 2774-3403
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86-Article Text-460-1-10-20220611_Pepadun_SENTIMENT ANALYSIS PROTOKOL KESEHATAN VIRUS CORONA DARI TWEET MENGGUNAKAN WORD2VEC MODEL DAN RECURRENT NEURAL NETWORK LEARNING.pdf Download (303kB) | Preview |
Abstract
Sentiment analysis is a computational study of opinion from various opinions, which is part of the work that conducts a review related to the computational treatment of opinions, sentiments, and perceptions of the text. To solve various problems in sentiment analysis, needed a good text representation method. In this study, a deep learning analysis was carried out using the Recurrent Neural Network (RNN) method and the Word2Vec Model as word embedding in sentiment classification. The sentiment dataset used comes from user reviews on Twitter (tweets) on the health protocols implemented by the public from the government's appeal. The results showed that the RNN model using sigmoid activation resulted in the greatest accuracy of 66%. The training process in this test uses 10 epochs and 32 batch sizes so that the precision value for negative sentiment is 54% and for positive sentiment is 67%.
| Item Type: | Article |
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer |
| Depositing User: | M.Kom. Dewi Asiah Shofiana |
| Date Deposited: | 25 Jul 2022 09:04 |
| Last Modified: | 25 Jul 2022 09:04 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/43603 |
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