Abstract

Advances in science and technology have changed this world. One of the data technologies that function in the world of learning during the COVID-19 pandemic is online education. Online education is used as a liaison between lecturers and students in an internet network that is accessed anytime. However, student learning outcomes in online and offline learning have not shown maximum results. Various obstacles arise that affect student learning outcomes online and offline during the COVID-19 pandemic. This study aims to predict the level of student understanding in online and offline learning. So that it can also help Pelita Indonesia universities to take the right policies to improve the quality of learning in the future. To solve the various problems above, an expert system is needed to predict. In the expert system used is the forward chaining method. The forward chaining method is a method that performs forward tracking, starting from a collection of facts and ending at a conclusion. So that the accuracy value is obtained. With the results of the accuracy test, it determines the level of understanding between online and offline learning.

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