Sentiment Analysis Using Convolutional Neural Network Method to Classify Reviews on Zoom Cloud Meetings Application Based on Reviews on Google Playstore

Rina Refianti, Novia Anggraeni


Zoom Cloud Meetings is an application that is used to conduct video conferencing. On the Google Play Store, the Zoom Cloud Meeting application received a rating of 3.8, with 500 million more downloads as of March 2021. The application has many advantages, such as not being disturbed by pauses in conversation and having good video and audio quality. The advantages possessed by these applications require development so that application services are getting better. For this reason, user reviews are needed to see user satisfaction with the application so that they can determine services that can be developed in the future. Based on this, this research was created to create a web-based application that can classify user reviews of the Zoom Cloud Meetings application using the Convolutional Neural Network (CNN) method and calculate the accuracy value. This application is built using the Flask framework and the Python programming language. Model training is carried out using the TensorFlow library. Applications that have been made are then tested using two stages of testing, namely system testing with black box and data testing. Based on system testing, it was found that the website can run well, and for data testing using test data, the accuracy result is 91.5%.


Classification, Sentiment Analysis, Convolutional Neural Network, Deep Learning

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