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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Cahya Damarjati
Jurusan Teknik Elektro dan Teknologi Informasi, Fakultas Teknik,Universitas Gadjah Mada Yogyakarta
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Sentiment Analysis on Social Media Using CNN-RNN Hybrid: A Case Study of Indonesian Presidential Candidate Riyadi, Slamet; Fayyadh Daffa; Cahya Damarjati; Megat Syahirul Amin Megat Ali
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 2, May 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i2.2125

Abstract

Research on sentiment analysis for Presidential Candidate 01 on social media cannot be ignored because there is no in-depth understanding of public perceptions and opinions circulating online. The CNN model is quite commonly used for sentiment analysis; however, this model still has quite low accuracy so modifications need to be made. This research aims to increase the accuracy of sentiment analysis through the application of a modified Convolutional Neural Network (CNN) method. The research process includes collecting tweet data related to Presidential Candidate 01 using crawling techniques, data preprocessing, sentiment labeling, data balancing, as well as dividing the dataset into training, validation and test data. The CNN model is modified with additional layers to improve the performance. The model is evaluated by measuring its accuracy, precision, recall, and F1 Score. The research results show that the modified CNN-RNN Hybrid model with the Upsampling method achieves an accuracy of 94% and F1 Score of 0.95, while the CNN-RNN Hybrid model has an accuracy of 86% and F1 Score of 0.82, the CNN Model has an accuracy of 90% and F1 Score of 0.88, and the RNN model has an accuracy of 88% and F1 Score of 0.84, which are higher compared to the Naïve Bayes and LSTM methods used in the previous research. Modifying the CNN method can significantly increase the accuracy of sentiment analysis for Presidential Candidate 01, so that it can become a more effective tool for understanding public perceptions and improving political campaign strategies.
Co-Authors Fayyadh Daffa Megat Syahirul Amin Megat Ali Slamet Riyadi