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Vol. 10, No. 2, May 2025

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Sentiment Analysis on Social Media Using CNN-RNN Hybrid: A Case Study of Indonesian Presidential Candidate

https://doi.org/10.22219/kinetik.v10i2.2125
Slamet Riyadi
Universitas Muhammadiyah Yogyakarta
Fayyadh Daffa
Universitas Muhammadiyah Yogyakarta
Cahya Damarjati
Universitas Muhammadiyah Yogyakarta
Megat Syahirul Amin Megat Ali
Universiti Teknologi MARA

Corresponding Author(s) : Slamet Riyadi

riyadi@umy.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 10, No. 2, May 2025

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.

Keywords

Sentiment Analysis Deep Learning Overfitting Oversampling Imbalanced Data
Riyadi, S., Fayyadh Daffa, Cahya Damarjati, & Megat Syahirul Amin Megat Ali. (2025). Sentiment Analysis on Social Media Using CNN-RNN Hybrid: A Case Study of Indonesian Presidential Candidate. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 10(2). https://doi.org/10.22219/kinetik.v10i2.2125
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Author Biography

Slamet Riyadi, Universitas Muhammadiyah Yogyakarta

Scopus: https://www.scopus.com/authid/detail.uri?authorId=6503991450

Google Scholar: https://scholar.google.com/citations?hl=en&user=bl1BHx8AAAAJ

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