ILKOM Jurnal Ilmiah
Vol 14, No 3 (2022)

Sentiment analysis of Indonesian reviews using fine-tuning IndoBERT and R-CNN

Herlina Jayadianti (Universitas Pembangunan Nasional Veteran Yogyakarta)
Wilis Kaswidjanti (Universitas Pembangunan Nasional Veteran Yogyakarta)
Agung Tri Utomo (Universitas Pembangunan Nasional Veteran Yogyakarta)
Shoffan Saifullah (Universitas Pembangunan Nasional Veteran Yogyakarta, AGH University of Science and Technology)
Felix Andika Dwiyanto (AGH University of Science and Technology, Universitas Negeri Malang)
Rafal Drezewski (AGH University of Science and Technology)



Article Info

Publish Date
19 Dec 2022

Abstract

Reviews are a form of user experience information on a product or service that can be used as a reference for potential consumers’ preferences to buy, use, or consume a product. They can be also used by business entities to find out public opinion about their product or the performance of their business products. It will be very difficult to process the review data manually and it will take a long time. Therefore, sentiment analysis automation can be used to get polarity information from existing reviews. In this study, IndoBERT with Recurrent Convolutional Neural Network (RCNN) was used to automate sentiment analysis of Indonesian reviews. The data used was a sentiment analysis dataset obtained from IndoNLU with sentiment consisting of negative sentiment, neutral sentiment, and positive sentiment. The results of the test showed that IndoBERT with the Recurrent Convolutional Neural Network (RCNN) had better results than the IndoBERT base. IndoBERT with Recurrent Convolutional Neural Network (RCNN) obtained 95.16% accuracy, 94.05% precision, 92.74% recall and 93.27% f1 score.

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Journal Info

Abbrev

ILKOM

Publisher

Subject

Computer Science & IT

Description

ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, ...