dc.contributor.author | K., Kadirgama | |
dc.contributor.author | M. M., Noor | |
dc.contributor.author | M. S. M., Sani | |
dc.contributor.author | M. M., Rahman | |
dc.contributor.author | M. R. M., Rejab | |
dc.contributor.author | M. Y., Taib | |
dc.contributor.author | Abdullah, Ibrahim | |
dc.contributor.author | Rosli, A. Bakar | |
dc.date.accessioned | 2010-08-23T09:10:41Z | |
dc.date.available | 2010-08-23T09:10:41Z | |
dc.date.issued | 2009-06-20 | |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/9027 | |
dc.description | MUCEET 2009 is organized by Malaysian Technical Universities Network (MTUN) comprising of Universiti Malaysia Perlis (UniMAP), Universiti Tun Hussein Onn (UTHM), Universiti Teknikal Melaka (UTeM) and Universiti Malaysia Pahang (UMP), 20th - 22nd June 2009 at M. S. Garden Hotel, Kuantan, Pahang. | en_US |
dc.description.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 70 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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Pahang (UMP) | en_US |
dc.relation.ispartofseries | Proceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCEET) 2009 | en_US |
dc.subject | Thermodynamics I | en_US |
dc.subject | Statistical | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Radial Basis Function Network (RBFN) | en_US |
dc.subject | Students -- Performance | en_US |
dc.subject | Malaysian Technical Universities Conference on Engineering and Technology (MUCEET) | en_US |
dc.title | Student performance analysis using artificial intelligent method | en_US |
dc.type | Working Paper | en_US |