Open AccessMultiple Correspondence Analysis Using Burt Matrix: A Study of Bandung Institute of Technology student Characteristics
Author(s) -
Adilan Mahdiyasa,
Udjianna S. Pasaribu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/598/1/012012
Subject(s) - matrix (chemical analysis) , interpretation (philosophy) , set (abstract data type) , process (computing) , computer science , data set , mathematics education , big data , data science , data mining , artificial intelligence , psychology , materials science , composite material , programming language , operating system
Student characteristics can provide important information for universities development. However, it is not easy to analyze or make interpretation related to student’s characteristic, because we have to deal with qualitative observation and large data set. This article recommends a new technique for Multiple Correspondence Analysis (MCA) that is appropriate when the data is big. We propose Burt matrix that makes the calculation process simpler and take less time. The new technique will be applied to questionnaire data on the features of students at the Bandung Institute of Technology (ITB), which is collected by The Students Loop (TSL) Company in 2017.