Sentiment Analysis on Shopee Product Reviews Using IndoBERT
| Autor: | Suhardi Aras, Muhammad Yusuf, Reinhard Yohanis Ruimassa, Elli Agustinus Billi Wambrauw, Elsa Bura Pala'langan |
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| Jazyk: | English<br />Indonesian |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Journal of Information Systems and Informatics, Vol 6, Iss 3, Pp 1616-1627 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2656-5935 2656-4882 |
| DOI: | 10.51519/journalisi.v6i3.814 |
| Popis: | A marketplace is a place in cyberspace where there are commercial activities between buyers and sellers. Products offered from the marketplace have reviews to review. Shopee is the most visited marketplace by people and offers various products. Product reviews can provide benefits for other consumers in assessing the products offered. By utilizing NLP technology in particular, this study can classify positive sentiment and negative sentiment in product review data. The IndoBERT model is a model that can be used in NLP technology by utilizing the relationship between each input and output element as well as the weights to be calculated simultaneously. By utilizing this technology, sentiment analysis on Shopee product reviews provides maximum accuracy until 93% with different training conditions. This provide that IndoBERT model can show that the performance of the indoBERT model in this research is very good. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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