The Level of Student Satisfaction with the Online Learning Process During a Pandemic Using the K-means Algorithm

Abstract

The number of cases of Covid-19 in this pandemic era is increasing and getting out of control every day. This triggers the Indonesian government to set policies on schools with online learning methods. Of course, online learning cannot ensure that it runs smoothly in all circles because several factors hinder the learning process. The difficulty of the internet network, limited quotas, unfamiliarity with the use of learning media, and an unsupportive environment for conducting online learning are the obstacles to ineffective online learning. The purpose of this study was to determine the level of satisfaction with online learning during the pandemic. This study uses quantitative research methods with a descriptive approach. Quantitative research methods will be processed into data mining using the K-Means Clustering Algorithm. The clustering process is carried out to get the results of clustering the level of student satisfaction. The dataset was obtained from the results of the questionnaire by submitting statements of satisfaction and dissatisfaction. The cluster type is based on high, medium, and low class. The test results obtained a value with the final iteration, namely the level of satisfied statements is categorized as high with a value of 11.79 compared to the dissatisfied statement, which is categorized as moderate with a value of 7.46. In contrast, for the low category level, there is no value of 0.00 cluster results state that the category is satisfied with online learning with a value of 9.33.

Students’ Preferences on Online Learning in the New Normal Period of the Covid-19 Pandemic

“…It leads to delay in assignments submission and interruption during the class (Hutauruk & Sidabutar, 2020). Similar to this argument, the difficulty of the internet network, limited quotas, unfamiliarity with the use of learning media, and a less supportive environment for conducting online learning are obstacles to the ineffectiveness of online learning (Arifin et al, 2021).…”

Application of the K-Means Clustering Algorithm to Determine Student Academic Ability Levels during Covid-19

“…The clusters with the best achievement category were cluster 3 with 1753 students, cluster 4 with 1496 students, cluster 2 with 676 students and cluster 1 with 330 students. Research conducted by (Arifin et al, 2021) research results the number of clusters formed there are 3. In the first cluster the category of satisfied with online learning is categorized as "high" with a value of 9.33 while the dissatisfied category is categorized as "low" with a value of 0.67.…”

Information system design for higher education evaluation based on student's perspective

“…Then Olmos-Gomez et al [10] researched quality at higher education institutions by comparing the satisfaction value between professors and students. Several studies are related to student satisfaction regarding online learning, especially during this pandemic era [11], [12], [13], [14], [15], [16], [17], [18]. However, we have not found any research that explicitly focuses on continuously evaluating the quality of higher education using information systems.…”