Risk modeling for Diploma in Business Studies (BM111) students at UiTM Johor / Adilah Mohd Din
Diploma in Business Studies (BM111) is among the first programme offered at Universiti Teknologi MARA (UiTM) Johor. It is a popular programme as indicated by the large number of students registered every semester since its introduction. However, over the July 2000 until December 2007 period, more th...
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Main Author: | |
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Format: | Thesis |
Language: | English |
Published: |
2012
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Online Access: | https://ir.uitm.edu.my/id/eprint/73971/1/73971.pdf https://ir.uitm.edu.my/id/eprint/73971/ |
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Summary: | Diploma in Business Studies (BM111) is among the first programme offered at Universiti Teknologi MARA (UiTM) Johor. It is a popular programme as indicated by the large number of students registered every semester since its introduction. However, over the July 2000 until December 2007 period, more than 10 percent of the students failed to complete their studies on time, which is within six semesters. Hence, it is necessary to identify the causes of this phenomenon so that appropriate actions can be taken to help the students at-risk. This study aims to identify factors that affect students' chances of graduating on time and the first two semesters' subjects that are most influential on the students' chances of graduating on time. This study also applies the data mining approach and employs decision tree, logistic regression and neural networks models to predict the graduation outcome. Based on initial investigations, there is evidence of difference in the risk of not graduating on time or failed to graduate between males and females, as well as between the July and December intakes. In addition, those who did not do well in the first semester courses, Financial Accounting (ACC1) and Mathematics for Business (MAT) and second semester courses, Microeconomics (ECO) and Cost of Accounting (ACC2) are most likely to fail to graduate or graduate on extended time. Hence, this study has proposed a methodology to predict at-risk students which can be adopted by other programmes and level of studies. The results indicate that the identified predictive models are accurate and can be deployed to identify students at-risk immediately after their first semester. The following courses of actions are recommended: (l) Higher SPM grades for Mathematics and Accounting for acceptance to BM111 programme; (2) Placement tests for Mathematics and Basic Accounting; (3) Pre-Accounting course for those without SPM Accounting; (4) Those who failed to score at least a B- grade for Financial Accounting and Mathematics for Business during the first semester should attend a Peer Tutorial Programme; (5) The effectiveness of the Peer-Tutorial Programme must be evaluated from time to time. |
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