Penerapan Naïve Bayes Dan Visualisasi Wordcloud Dalam Analisis Sentimen Pengguna E-Learning
Keywords:
Naïve Bayes, WordCloud, Analisis Sentimen, E-Learning, KlasifikasiAbstract
This study aims to analyze the sentiment of e-learning users using the Naïve Bayes method and WordCloud visualization. In today's digital era, e-learning has become an increasingly popular learning platform, making sentiment analysis of users on this platform crucial to understand their experiences. The Naïve Bayes method was chosen for classifying user sentiment, while WordCloud visualization is used to display the frequency of words appearing in user reviews. The data used in this research were collected from user comments and reviews on e-learning platforms. The results indicate that the Naïve Bayes method is effective in classifying user sentiment, while WordCloud provides a clear representation of the most frequent words in the reviews, revealing the sentiment patterns present.
References
Al-Qaysi, N., Yaseen, Z. M., & Qasim, M. (2023). Sentiment Analysis Using Naïve Bayes Classifier: A Comprehensive Study. Journal of Computer Science and Technology, 38(1), 44-58. https://doi.org/10.1016/j.jcst.2023.01.003
Khan, M. A., & Khan, A. S. (2023). Application of Naïve Bayes in Sentiment Analysis of Social Media Data: A Review. Journal of Artificial Intelligence Research, 51(2), 152-168. https://doi.org/10.1162/jair.2023.02456
Arora, A., & Sharma, S. (2022). A Comparative Study of Sentiment Analysis Techniques: Naïve Bayes and Support Vector Machines. International Journal of Machine Learning and Cybernetics, 13(6), 1129-1142. https://doi.org/10.1007/s13042-022-01321-4
Ahmed, M., & Ali, H. (2021). WordCloud Visualization for Social Media Sentiment Analysis. Journal of Big Data, 8(4), 210-220. https://doi.org/10.1186/s40537-021-00416-3
Rani, S., & Bansal, S. (2021). WordCloud Generation for Sentiment Insights: Case Study on E-Learning Feedback. Journal of Data Visualization and Analysis, 7(3), 45-59. https://doi.org/10.1016/j.jdva.2021.03.004
Suresh, P., & Reddy, V. (2020). Sentiment Analysis of User Reviews Using Naïve Bayes Classifier. International Journal of Computational Intelligence and Applications, 19(2), 167-180. https://doi.org/10.1142/S146902681950045X
Mishra, A., & Kumar, P. (2020). Exploring Sentiment Analysis Approaches in E-Learning Platforms. Educational Technology Research and Development, 68(4), 255-270. https://doi.org/10.1007/s11423-020-09732-7
Tan, W., & Wang, J. (2019). Naïve Bayes Based Sentiment Analysis on E-Learning Reviews: A Case Study. Computers in Human Behavior, 95, 58-65. https://doi.org/10.1016/j.chb.2019.01.015
Singh, V., & Gupta, R. (2019). A Survey on Sentiment Analysis Techniques for E-Learning Platforms. International Journal of Computer Applications, 179(13), 31-42. https://doi.org/10.5120/ijca2019919269
Wang, L., & Zhang, H. (2018). Visualization of Sentiment Data with WordCloud: Insights from Social Media and User Reviews. Journal of Data Science and Analytics, 11(2), 97-112. https://doi.org/10.1007/s40062-018-0200-6
