Similarity : Sentiment Analysis using Recurrent Neural Network

Kurniasari, Lilis and Setyanto, Arif (2020) Similarity : Sentiment Analysis using Recurrent Neural Network. IOP Publishing, Bukittinggi.

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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:	Other
Subjects:	Q Science > QC Physics T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Civil Engineering and the Environment
Depositing User:	Tri Yuliani
Date Deposited:	13 May 2022 02:02
Last Modified:	13 May 2022 02:02
URI:	http://repository.unu-jogja.ac.id/id/eprint/200

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