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All Journal Jurnal Sistim Informasi dan Teknologi
Abdi Rahim Damanik
Universitas Putra Indonesia YPTK Padang
Computer Science & IT Decision Sciences, Operations Research & Management

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Prediksi Tingkat Kepuasan dalam Pembelajaran Daring Menggunakan Algoritma Naïve Bayes Abdi Rahim Damanik; S Sumijan; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (454.573 KB) | DOI: 10.37034/jsisfotek.v3i3.49

Abstract

The growth of learning at this time is influenced by advances in data and communication technology. One of the data technologies that functioned in the world of learning during the COVID-19 pandemic was online education. Online education is used as a liaison between lecturers and students in an internet network that can be accessed at any time. The online media used are Whatsapp, Google Classroom, Google Meet, Cloud x and the Zoom application. This research aims to predict the level of student satisfaction in online education as well as to distribute donations to large academies in making policies related to improving the quality of education online. The information used was obtained by distributing questionnaires to 110 students of the 2020/2021 class. The parameters in the questionnaire are lecturer communication, online education atmosphere, student evaluation, module delivery. Naïve Bayes is a prediction method for finding simple probabilities based on the Bayes theorem with a strong assumption of independence. Rapid Miner is one of the tools used for testing information and viewing the results of accuracy based on revolutionary information. The results of the test using 80 training information and 30 testing information show very good accuracy.
Co-Authors Gunadi Widi Nurcahyo S Sumijan