Analysis of problems on zoom cloud meetings application based on end user reviews using text mining and fishbone diagram.

In the era of the industrial revolution 4.0 as it is today, there has been a rapid technological development that has penetrated into various fields, especially in the telecommunications sector. One of the advances in telecommunications technology is a technology that can support audio and video communication simultaneously and in real-time, namely video conferencing. One of the companies engaged in video conference-based telecommunications services is Zoom Technologies, Inc. which launched the Zoom cloud meetings application which can be downloaded via the Google Play Store. However, until December 2020 the Zoom Cloud Meetings application only received a rating of 3.6 stars out of a total rating of 5.0. Therefore, there is a need for research related to Zoom Cloud Meetings using user reviews from the Google Play Store. The reviews analyzed in the study amounted to 75,454 which had been classified into positive and negative sentiment classes using the Naïve Bayes Classifier algorithm and association rules were carried out. Classification with Naïve Bayes Classifier with training data of 85% and test data of 15% produces an optimum accuracy of 86.67%. From the results of the review analysis, eight key words were found, namely, "meeting", "video", "audio", "class", "work", "update", "time" and "connect". Some of the causes of problems include connecting to meetings for a long time, complaints about the quality of sound, video and limited time for free users, and problems related to applications that cannot be run. [ABSTRACT FROM AUTHOR]