UMP Institutional Repository

Student Performance Analysis Using Artificial Intelligent Method

M. M., Noor and K., Kadirgama and M. S. M., Sani and M. R. M., Rejab and M. M., Rahman and M. Y., Taib (2009) Student Performance Analysis Using Artificial Intelligent Method. In: Malaysian Technical Universities Conference on Engineering and Technology, 20-22 June 2009 , MS Garden Hotel, Kuantan, Pahang, Malaysia. .

[img]
Preview
PDF (Word to PDF conversion (via antiword) conversion from application/msword to application/pdf)
2009_P_MUCEET09_Std_M.M.Noor_K.Kadirgama-conference-done-.pdf

Download (345kB)

Abstract

Measuring of academic performance of students is challenging since student performance is product of socio-economic, psychological and environmental factors. This paper discussed the neural network method were used to measure student performance in Thermodynamic at Faculty of Mechanical Engineering, University Malaysia Pahang (UMP). Randomly 65 mechanical engineering students were picked to analysis their performance in these subjects with 5 variables which are Test1, Test 2, Final Examination, assignment and Quizzes. The analysis was done to measure the student performance in Thermodynamic I which final grade was used as the tools. The models show that Test 1 and Test 2 plays major role in the student final grade. Meanwhile assignments and quizzes play as a booster to their performances. The artificial intelligent model can be used for further investigate of the subject performance with include more predictor such as age, CGPA, gender and etc.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Proceeding Mohd Yusof Bin Taib (M. Y. Taib) Muhamad Mat Noor (M. M. Noor) Dr. Kumaran Kadirgama (K. Kadirgama) Dr. Mohd Ruzaimi Mat Rejab (M. R. M. Rejab) Profesor Dr. Md. Mustafizur Rahman (M. M. Rahman) Mohd Shahrir Bin Mohd Sani (M. S. M. Sani)
Uncontrolled Keywords: Thermodynamics I, Statistical, Genetic Algorithms, Radial Basis Function Network (RBFN)
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Zairi Ibrahim
Date Deposited: 24 Aug 2011 04:01
Last Modified: 31 Jan 2018 01:45
URI: http://umpir.ump.edu.my/id/eprint/1445
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item