A study on Students’ performance in compliance with Industry requirements using Data Mining Techniques

Authors

  • Justin Rajasekaran University of Technology and Applied Sciences, Shinas, Oman

DOI:

https://doi.org/10.5281/zenodo.7384567%20

Keywords:

Academic performance, prediction, Decision making, Data Mining, Cluster

Abstract

Education is one of the best aspects of our life which makes the student to learn the value of education. It makes the student technically sound enough with the confident to face the world. For the academic institution and the industry play a vital role in each student’s education. To meet the industry standard, it is important to identify student’s performance becomes challenging due to high value of educational databases. So, it is necessary to analyze and monitor the student performance in order to meet industry requirements. This paper identifies suitable method for predicting the performance of the students in Oman using data mining techniques.

Author Biography

Justin Rajasekaran, University of Technology and Applied Sciences, Shinas, Oman

Justin Rajasekaran, received the Master degree in Computer Application from Madurai Kamaraj University, Tamil Nadu, Chennai, in 1998. He is currently working as a Lecturer at University of Technology and Applied Sciences-Shinas, Sultanate of Oman. His research interest includes data mining, big data analytics, block chain technology, Data Privacy & Security, Software Quality and Testing, and Information Security. He can be contacted at email: Justin.rajasekaran@shct.edu.om

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Published

2022-12-07

How to Cite

Justin Rajasekaran. (2022). A study on Students’ performance in compliance with Industry requirements using Data Mining Techniques. International Journal of Information Technology, Research and Applications, 1(3), 1–5. https://doi.org/10.5281/zenodo.7384567

Issue

Section

Regular Issue