Video conferencing is an application that allows users to communicate, hold meetings, learn and share information. Until now, there have been many video conferencing applications used, such as Zoom, Google Meet, and Microsoft Teams. Of course, each application has a review of the application used. With reviews, other users can consider and find out more about the application used. However, because the number of reviews on the internet is very large, sentiment analysis is needed to be able to classify into positive, neutral, or negative sentiments. In this study, around 700-1000 review data for each application were taken from the Play Store. The review data uses Indonesian and is taken based on the latest application version. Before being used, the data needs to be labeled and preprocessed first to be able to classify sentiment. The processing process uses TF-IDF word weighting, Naïve Bayes classification, and confusion matrix as evaluation materials. Later, the review data from the three applications will be processed separately. The zoom meeting application generated 31.33% positive sentiment (125 review data), 7.77% negative sentiment (31 review data) and 60.90% neutral sentiment (243 review data) from a total of 399 reviews. The Google Meet application generated 28.05% positive sentiment (260 review data), 4.10% negative sentiment (38 review data) and 67.85% neutral sentiment (629 review data) from a total of 927 reviews. The Microsoft Teams application generated 22.95% positive sentiment (137 review data), 11.06% negative sentiment (66 review data) and 66.00% neutral sentiment (394 review data) from a total of 597 reviews. In addition, the accuracy value of the three applications was also obtained, namely Zoom Meeting obtained a percentage of 85%, Google Meet obtained a percentage of 90%, and Microsoft Teams obtained a percentage of 89%.

Video conference merupakan aplikasi yang memungkinkan pengguna untuk berkomunikasi, melakukan rapat, belajar dan berbagi informasi. Hingga saat ini, sudah banyak aplikasi video conference yang digunakan, seperti Zoom, Google Meet, dan Microsoft Teams. Tentunya disetiap aplikasi terdapat ulasan mengenai aplikasi yang digunakan. Dengan adanya ulasan, maka pengguna lain dapat mempertimbangkan dan mengetahui lebih jauh terkait aplikasi yang digunakan. Namun karena jumlah ulasan di internet sangat banyak, maka diperlukan analisis sentimen untuk dapat mengklasifikasikan ke dalam sentimen positif, netral, atau negatif. Pada penelitian ini, kisaran 700-1000 data ulasan setiap aplikasi diambil dari Play Store. Data ulasan tersebut menggunakan Bahasa Indonesia dan diambil berdasarkan versi aplikasi terbaru. Sebelum digunakan, data perlu dilabeli dan dilakukan preprocessing terlebih dahulu untuk dapat melakukan klasifikasi sentimen. Proses pengerjaannya menggunakan pembobotan kata TF-IDF, klasifikasi Naïve Bayes, dan confusion matrix sebagai bahan evaluasi. Nantinya data ulasan dari ketiga aplikasi tersebut akan diproses secara terpisah. Pada aplikasi zoom meeting menghasilkan 31.33% sentimen positif (125 data ulasan), 7.77% sentimen negatif (31 data ulasan) dan 60.90% sentimen netral (243 data ulasan) dari jumlah total ulasan sebanyak 399 data. Pada aplikasi google meet menghasilkan 28.05% sentimen positif (260 data ulasan ), 4.10% sentimen negatif (38 data ulasan) dan 67.85% sentimen netral (629 data ulasan) dari jumlah total ulasan sebanyak 927 data. Pada aplikasi microsoft teams menghasilkan 22.95% sentimen positif (137 data ulasan), 11.06% sentimen negatif (66 data ulasan) dan 66.00% sentimen netral (394 data ulasan) dari jumlah total ulasan sebanyak 597 data. Selain itu, juga didapatkan nilai akurasi dari ketiga aplikasi yaitu Zoom Meeting didapat persentase sebesar 85%, Google Meet didapat dpersentase sebesar 90%, dan Microsoft Teams didapat persentase sebesar 89%.