Sentiment Analysis using Recurrent Neural Network in indonesian language
Lilis Kurniasari (a*), Arief Setyanto (b)
a) Magister Teknik Informatika, AMIKOM Yogyakarta
Jl. Ring Road Utara, Condong Catur, Sleman, Yogyakarta
rainforest02[at]gmail.com
b) Magister Teknik Informatika, AMIKOM Yogyakarta
Jl. Ring Road Utara, Condong Catur, Sleman, Yogyakarta
arief_s[at]amikom.ac.id
Abstract
This study aims to measure the accuracy of the sentiment analysis classification model using deep learning and neural networks. This study uses 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 test the model through experiments. In this study, we use two classification (positive and negative). Experiments are carried out using training data sets and test set data sourced from the Travelokas website. The result show that the model shows outstanding results and reaches about 91,9%.
Keywords: Sentiment Analysis, Deep Learning, RNN, word2vec
Topic: International Symposium of Engineering, Technology, and Health Sciences