A predictive model of the enrolment in the key subject of STEM education using the machine learning paradigm

• Main Authors: Chuan, Zun Liang, Norhayati, Rosli, Fam, Soo Fen, Tan, Ee Hiae
• Format: Conference or Workshop Item
• Language: English; English
• Published: Academic International Dialogue (AID) 2021
• Subjects: LB1603 Secondary Education. High schools; QA Mathematics
• Online Access: http://umpir.ump.edu.my/id/eprint/32122/1/IMIC%202021.pdf; http://umpir.ump.edu.my/id/eprint/32122/7/A%20predictive%20model%20of%20the%20enrolment%20in%20the%20key%20subject%20of%20STEM%20education%20.pdf; http://umpir.ump.edu.my/id/eprint/32122/; https://imicaidconference.weebly.com/imic-2021-e-proceeding.html

The presence of a global health crisis on coronavirus pandemic (COVID-19) has been accelerated the global uptakes the transformation towards the digital economy. Consequently, the rapid digital transformation has risen the demands of technologically competent workforces in which open the big doors f...