Jurnal Natural
Volume 22 Number 1, February 2022

Application of PLS SEM in Evaluations of Mathematics Statistics II Course Online Learning

IZZATI RAHMI (Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University)
MAHDHIVAN SYAFWAN (Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University)
HAZMIRA YOZZA (Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University)
IQBAL HAMONANGAN (Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University)
FRILIANDA WULANDARI (Department of Mathematics, Faculty of Mathematics and Natural Science, Andalas University)



Article Info

Publish Date
26 Feb 2022

Abstract

The impact of the COVID-19 pandemic on the education sector includes the learning system that cannot be conducted directly (offline). With the change in the learning system, it is necessary to evaluate whether the implemented online learning system can run well and provide results as expected. The level of student satisfaction is one of the factors that can be used to evaluate online learning. This study analyzed the student satisfaction level with online learning for the Mathematics Statistics II course at the Mathematics Department of Andalas University, related to service quality by lecture and the level of student understanding. Data analysis was conducted using causal modeling, namely Partial Least Square Structural Equations Modeling (PLS-SEM). By using The PLS-SEM, it is known that there is a significant and positive effect of service quality on student satisfaction in the Mathematics Statistics II course. In addition, the service quality also affects the understanding level significantly and positively. However, the level of student understanding has no significant effect on the level of student satisfaction. The coefficient of determination (R2) from the structural model of student satisfaction toward the Mathematics Statistics II course online learning is 0.774. This value indicates that the resulting model is good because it has relatively high accuracy.

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Journal Info

Abbrev

natural

Publisher

Subject

Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Earth & Planetary Sciences Energy Immunology & microbiology Neuroscience Physics

Description

Jurnal Natural (JN) aims to publish original research results and reviews on sciences and mathematics. Jurnal Natural (JN) encompasses a broad range of research topics in chemistry, pharmacy, biology, physics, mathematics, statistics, informatic and ...