Muhammad mahrus zain
Politeknik Caltex Riau

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Analisis Sentimen Pendapat Masyarakat Mengenai Vaksin Covid-19 Pada Media Sosial Twitter dengan Robustly Optimized BERT Pretraining Approach Muhammad mahrus zain
Jurnal Komputer TerapanĀ  Vol. 7 No. 2 (2021): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v7i2.4782

Abstract

On March 11, 2020, the World Health Organization (WHO) officially declared COVID-19 a global pandemic. The spread of this virus already existed in 2019 in the city of Wuhan, China. The government officially stipulates a Presidential Regulation (PERPRES) on Vaccine Procurement and Vaccination Implementation in the Context of Overcoming the Coronavirus Disease Pandemic. The vaccination activity plan must also consider various inputs, among them is by looking at how the response and public opinion to the vaccination discourse. By utilizing data from Twitter social media, this study aims to analyze the public's response to the vaccination discourse by classifying the response into positive and negative responses. Furthermore, public opinion grouping will also be carried out using the pre-trained Indonesian RoBERTa Base Sentiment Classifier model to find out the sentiments of the Covid-19 vaccination topic discussed by the community. The results of the analysis showed that the public gave more negative responses to the discourse (24.7%) compared to positive responses (5.7%) with the remaining neutral responses (69.6%). Sentiment words that occur most often also indicate more words with negative sentiments than words with positive sentiments. The average results of the prediction accuracy of the application of the pre-trainer model on the positive label are 84%, Neutral 97% and Negative 93%.
Pemanfaatan ReactJS dan Protokol MQTT untuk Visualisasi Sinyal Lampu dan Notifikasi secara Waktu Nyata pada Sistem Pemonitor APILL di Kota Pekanbaru Ardianto Wibowo; Muhammad Mahrus Zain
Jurnal Komputer TerapanĀ  Vol. 7 No. 2 (2021): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v7i2.5108

Abstract

The majority of signalized intersections in Pekanbaru city are still regulated by analog controllers. The main problem that occurs with this condition is the occurrence of long traffic jams if there is damage to the traffic light controller. Thus, the Pekanbaru City Transportation Department cannot act immediately once a problem occurs. Related to these problems, an integrated system has been developed that functions to manage and monitor traffic light conditions in real time. This research is focused on discussing the use of ReactJS and MQTT. ReactJS is used to display traffic light light signal data and provide real time notifications into a web browser. Meanwhile, MQTT is used as a medium to manage data communication between the detection module installed on the traffic light controller in the field to the Back-End server. This data is then displayed to the web browser via React JS. With the solution in this research, it is hoped that the Pekanbaru City Transportation Office can find out the problems of traffic light lamps in the field quickly, so that they can immediately take the relevant actions needed.