Student academic performance analysis using fuzzy C-means clustering

The Indonesian Operations Research Association (IORA) - International Conference on Operations Research 2016

Rosadi, R.^1 ; Akamal^1 ; Sudrajat, R.^1 ; Kharismawan, B.^2 ; Hambali, Y.A.^3

Department of Computer Science, Padjadjaran University, Sumedang

45363, Indonesia^1

Department of Mathematics, Padjadjaran University, Sumedang

45363, Indonesia^2

Master Stud. of STEI, Institute of Technology Bandung, Bandung

40132, Indonesia^3

关键词: Academic performance;    Clustering methods;    Data relationships;    Fuzzy C means clustering;    Fuzzy C-means algorithms;    Grade point average;    Student performance;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/166/1/012036/pdf
DOI  :  10.1088/1757-899X/166/1/012036

来源: IOP

【 摘 要 】

Grade Point Average (GPA) is commonly used as an indicator of academic performance. Academic performance evaluations is a basic way to evaluate the progression of student performance, when evaluating student's academic performance, there are occasion where the student data is grouped especially when the amounts of data is large. Thus, the pattern of data relationship within and among groups can be revealed. Grouping data can be done by using clustering method, where one of the methods is the Fuzzy C-Means algorithm. Furthermore, this algorithm is then applied to a set of student data form the Faculty of Mathematics and Natural Sciences, Padjadjaran University.