TY - JOUR
T1 - The accuracy of transfer learning using neural network method for sentiment analysis problem on Indonesian tweets
AU - Augustizhafira, A. N.
AU - Murfi, H.
AU - Ardaneswari, G.
N1 - Publisher Copyright:
© 2021 Journal of Physics: Conference Series.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1/12
Y1 - 2021/1/12
N2 - In this paper, sentiment analysis is applied to one social media called Twitter. Sentiment analysis is categorized as a classification problem that can be solved using one of machine learning methods, namely Neural Network. If machine learning is applied, it is necessary to rebuilt the model from scratch using new training data that requires manual labelling process. Hence, it is better to apply other learning besides machine learning, such as transfer learning. The simulation in this research yielded an accuracy of transfer learning using Neural Network which will be tested by N-grams (bigram and trigram) feature and one of feature selection method, namely Extra-Trees Classifier. The highest value of transfer learning accuracy is obtained when one hidden layer, 250 neurons on hidden layer, and tanh activation function are used. The use of feature selection method in simulation can also improve the transfer learning performance, so that the accuracy value is higher than the one that does not use feature selection method.
AB - In this paper, sentiment analysis is applied to one social media called Twitter. Sentiment analysis is categorized as a classification problem that can be solved using one of machine learning methods, namely Neural Network. If machine learning is applied, it is necessary to rebuilt the model from scratch using new training data that requires manual labelling process. Hence, it is better to apply other learning besides machine learning, such as transfer learning. The simulation in this research yielded an accuracy of transfer learning using Neural Network which will be tested by N-grams (bigram and trigram) feature and one of feature selection method, namely Extra-Trees Classifier. The highest value of transfer learning accuracy is obtained when one hidden layer, 250 neurons on hidden layer, and tanh activation function are used. The use of feature selection method in simulation can also improve the transfer learning performance, so that the accuracy value is higher than the one that does not use feature selection method.
KW - Extra-trees classifier
KW - N-gram
KW - Neural network
KW - Sentiment analysis
KW - Transfer learning
UR - http://www.scopus.com/inward/record.url?scp=85100712562&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1725/1/012015
DO - 10.1088/1742-6596/1725/1/012015
M3 - Conference article
AN - SCOPUS:85100712562
SN - 1742-6588
VL - 1725
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012015
T2 - 2nd Basic and Applied Sciences Interdisciplinary Conference 2018, BASIC 2018
Y2 - 3 August 2018 through 4 August 2018
ER -