Vol.11, No.3, August 2022.                                                                                                                                                                              ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Sentiment Analysis of COVID-19 using Multimodal Fusion Neural Networks


Ermatita Ermatita, Abdiansah Abdiansah, Dian Palupi Rini, Fatmalina Febry


© 2022 Ermatita Ermatita, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 11, Issue 3, Pages 1316-1321, ISSN 2217-8309, DOI: 10.18421/TEM113-41, August 2022.


Received: 29 March 2022.

Revised:   10 August 2022.
Accepted: 16 August 2022.
Published: 29 August 2022.




The purpose of this study creates a Sentiment Analysis model of COVID-19 using Multimodal Fusion Neural Networks in real time to model and visualize COVID-19 in Indonesia. This study obtained 87 percent accuracy using the Multimodal Fusion Neural Networks model, a higher 5 percent than the benchmarking model Convolutional Neural Networks. This study proves that the sentiment model built is quite promising and relevant to be implemented.


Keywords – Multimodal Fusion Neural Networks, COVID-19, Sentiment Analysis.



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