ABSTRACT
Collaboration is a very important factor in doing a task. Due to the COVID-19 pandemic, face-to-face collaboration has turned into virtual collaboration, but its implementation has encountered many obstacles in the field. This study aims to examine the influence of factors that support virtual collaboration (VC), including technology support (DT), digital literacy (DL), cultural intelligence (CQ), and virtual leadership (VL), as antecedents of VC in the world of High Education. Respondents consisted of 216 universities with a total sample of 216 lecturers who were selected using the purposive sampling method. The research questionnaire was sent to the relevant email address using Google Form. The results showed that the four antecedent variables had a significant influence with the ability to explain 62.3% of the VC. Theoretically, the research has contributed in the form of a virtual collaboration model that has been empirically tested in the field. In addition, this model has expanded the factors that influence VC from several previous studies. Practically, the results of this research can be useful for university administrators who want to increase collaboration between their lecturers, especially in the fields of teaching, research and publications. In this context, the antecedent factors of this virtual collaboration model can be taken into consideration. © 2022, Success Culture Press. All rights reserved.
ABSTRACT
At the end of 2019, the world was hit by the COVID-19 virus, which caused a pandemic. Indonesia has become one of the countries that are affected by this pandemic. To control the COVID-19 pandemic, the government has made various efforts, one of which is the use of the PeduliLindunig app. To access the PeduliLindungi app, the public can download it from Google Play. Google Play enables its users to write reviews on the apps that have been downloaded. This study aims to determine the sentiment analysis on the PeduliLindungi application on Google Play using the Random Forest Algorithm with SMOTE. Based on this study, public sentiment towards the PeduliLindungi app on Google Play tends to be negative. The Random Forest and SMOTE algorithms are used to classify sentiment in this study. The implementation of Random Forest and SMOTE resulted in 71% accuracy, 70% recall, and 70% precision. © 2022 IEEE.