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Implementation of Convolutional Neural Network Algorithm in Sentiment Analysis on User Reviews Of MySAPK Application
Subject area: Science,Engineering and Technology · Area of research: Computer Science
Abstract
BKN launched the MySAPK application to independently update personal data and history. Sentiment analysis was conducted to evaluate the quality and performance of the MySAPK application. The data used is a user review of the MySAPK application using the Convolutional Neural Network (CNN) algorithm.The research method consists of data collection, labeling, preprocessing, processing, testing, and evaluation. The Convolutional Neural Network (CNN) algorithm produces an accuracy rate of 90% in the testing process, with positive sentiments from its users.
Keywords
Sentiment Analysis, Convolutional Neural Network (CNN), MySAPK.
References
[1] Sharma, A. K., Chaurasia, S., and Srivastava, D. K, ―Sentimental Short Sentences Classification by Using CNN Deep Learning Model with Fine Tuned Word2Vec,‖ Procedia Computer Science, India, 2019, pp. 1139–1147.
[2] P. Ce and B. Tie, ―An analysis method for interpretability of CNN text classification model,‖ Futur. Internet, vol. 12, no. 12, pp. 1–14, Dec 2020.
[3] Listyarini, S. N. and Anggoro, D. A, ―Analisis Sentimen Pilkada di Tengah Pandemi Covid-19 Menggunakan Convolution Neural Network (CNN),‖ Jurnal Pendidikan dan Teknologi Indonesia, vol.1, no.7, pp. 261–268, Jul 2021.
[4] Qosim, A. L. et al, ―Analysis Classification Opinion of Policy Government Announces Cabinet Reshuffle on YouTube Comments Using 1D Convolutional Neural Networks,‖ in 3rd 2021 East Indonesia Conference on Computer and Information Technology EIConCIT, Surabaya, 2021, pp. 30–35.
How to cite this paper
@article{1703301,
author = {Vanessia Putriadiva, Marliza Ganefi Gumay},
title = {Implementation of Convolutional Neural Network Algorithm in Sentiment Analysis on User Reviews Of MySAPK Application},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {9},
pages = {459-462},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1703301.pdf},
abstract = {BKN launched the MySAPK application to independently update personal data and history. Sentiment analysis was conducted to evaluate the quality and performance of the MySAPK application. The data used is a user review of the MySAPK application using the Convolutional Neural Network (CNN) algorithm.The research method consists of data collection, labeling, preprocessing, processing, testing, and evaluation. The Convolutional Neural Network (CNN) algorithm produces an accuracy rate of 90% in the testing process, with positive sentiments from its users.},
keywords = {Sentiment Analysis, Convolutional Neural Network (CNN), MySAPK.},
month = {March},
}