Prediction of Student Study Duration Using Multiple LinearRegression Method

Abstract

Data mining is a process of extracting valuable and
meaningful information from large or complex data sets. In
the field of education, data mining can be used to predict the
length of study of students by identifying factors that affect
the length of study of students. This research aims to predict
the length of study of students and to find out the most
influential variables in completing the length of study. The
method used in this research is the Multiple Linear
Regression method. Training data as much as 292 data is
taken from data on graduates from 2016 - 2018. While the
testing data is taken from the active student data class of
2018 as much as 148 data. The model formed will be
evaluated to determine the accuracy and RMSE values. The
results showed that the Multiple Linear Regression method
succeeded in carrying out the prediction process optimally
with a percentage accuracy value of 85%, and an RMSE
value of 0.76, which means that the error rate of this model is
very low. Based on the resulting coefficient value, the SKS
variable is the most influential variable in the length of study
of students.