ANALISIS TINGKAT KEPUASAN PENGGUNA GOOGLE CLASSROOM DALAM PEMBELAJARAN ONLINE MENGGUNAKAN ALGORITMA NAÏVE BAYES - Fildzah Nadya Arieni; Eka Irawan; Dedi Suhendro (Lembaga Pengembangan Kinerja Dosen, 2022)
SMK Negeri 3 Pematangsiantar is one of the schools affected by the COVID-19 pandemic, which at that time the whole world was facing an outbreak of this infectious disease. The Covid-19 pandemic that was hitting the whole world at that time, required all students and students to carry out the online learning process in order to prevent the spread of the Covid-19 virus. This study aims to classify the level of satisfaction of Google classroom users using nave Bayes data mining techniques. Sources of data obtained from questionnaires given to students randomly as many as 100 students. The criteria used as Google Classroom user satisfaction include: system quality, service, information, usage, user satisfaction. The model generated by researchers and Rapid Miner Software with training data as much as 75 data. There are 25 test data that are processed in Rapid Miner 5.3. get test results with an accuracy of 96.00%, namely 15 satisfied users and 10 dissatisfied users.