Sentiment Analysis using Recurrent Neural Network

Kurniasari, Lilis and Setyanto, Arif (2020) Sentiment Analysis using Recurrent Neural Network. IOP Conf. Series: Journal of Physics: Conference Series.

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Abstract

This study aims to measure the accuracy of the sentiment analysis classification model using deep learning and neural networks. This study used the algorithm Recurrent Neural Network (RNN) and Word2vec. No previous research has used this model to analyze sentiments written using Indonesian language so that the level of accuracy is unknown. The research began by making a classification model of sentiment analysis. Then, the model was tested through experiments. In this study, They used two classifications (positive and negative). Experiments are carried out using training data sets and the test used data sets sourced from Traveloka theybsite. The result shows that the model presents outstanding results and reaches about 91.9%.

Item Type:	Article
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Depositing User:	Tri Yuliani
Date Deposited:	22 Apr 2022 04:54
Last Modified:	22 Apr 2022 04:54
URI:	http://repository.unu-jogja.ac.id/id/eprint/167

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