Abstract
Blended Learning combines teaching and learning activities in the classroom and online teaching. In its implementation, this learning method requires a lot of data. One of them is the student's online test score data which can be used as an evaluation of learning. For this reason, in this study, data mining is used to determine the results of online student examinations as well as to determine student interest in learning about the implementation of Blended Learning. Data mining techniques are used in the logs of online learning session results, so that one can assess the online learning system used. By assessing the system, it can be identified which students who have studied hard and those who have not studied in the online exam. The series data used are student test score data on the State Polytechnic of Malang Learning Management System (LMS). The student score dataset is arranged based on variables in the Educational Process Mining (EPM) Dataset of UCI, which are obtained from teacher’s assignments. In addition, data mining classification is used to determine student interest in learning towards blended learning. In the process of data mining, comparative analysis is carried out using the features of the RapidMiner tool to carry out the process of student data for training and data validation. This process uses several algorithms along with student data which is divided into two sets for training and validation. From the results of data mining calculations produce a classification with minimum errors. From the test, the resulting linear regression algorithm has RMSE 0.000 and SE 0.000, while the neural network algorithm has RMSE 0.525 and SE 0.275.
Highlights
In this era of higher education, the role of blended learning has provided considerable benefits [1][2][3]
The student score dataset variable used refers to the Educational Process Mining (EPM) Dataset of UCI and the processing and analysis of the score datasets uses the RapidMiner tool
From these activities students are trained and given the opportunity to strengthen learning through content and assessments that exist on the Learning Management System (LMS) system
Summary
In this era of higher education, the role of blended learning has provided considerable benefits [1][2][3]. The purpose of the blended learning initiative is to provide assistance that enables lecturers to help the instructors themselves in the teaching and learning process, with the aim of increasing students' understanding of face-to-face teaching and learning in class [4][5]. Data mining can help the educational institution in evaluating the education system policy, and in finding students' learning interests towards the learning system [10]. The data mining classification method is applied to process and analyze data on IT Department student test scores in the Learning Management System (LMS) of State Polytechnic of Malang. The results of the study produce calculations from the data mining process, these results reflect students' interest in the implementation of blended learning in teaching and learning activities
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