1. M. of Education Malaysia, National higher education strategic plan (2015). URL http://www.moe.gov.my/v/pelan-pembangunan-pendidikan-malaysia-2013-2025.
2. U. bin Mat, N. Buniyamin, P.M. Arsad, R. Kassim, An overview of using academic analytics to predict and improve students’ achievement: A proposed proactive intelligent intervention, in: Engineering Education (ICEED), 2013 IEEE 5th Conference on, IEEE, 2013, pp. 126-130.
3. Z. Ibrahim, D. Rusli, Predicting students academic performance: comparing artificial neural network, decision tree and linear regression, in: 21st Annual SAS Malaysia Forum, 5th September, 2007.
4. C. Romero, S. Ventura, Educational data mining: A review of the state of the art, Trans. Sys. Man Cyber Part C 40 (6) (2010) 601-618. doi:10.1109/TSMCC. 2010.2053532. URL http://dx.doi.org/10.1109/TSMCC. 2010.2053532.
5. D. M. D. Angeline, Association rule generation for student performance analysis using apriori algorithm, The SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 1 (1) (2013) p12-16.