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dc.contributor.authorK., Kadirgama
dc.contributor.authorM. M., Noor
dc.contributor.authorM. S. M., Sani
dc.contributor.authorM. M., Rahman
dc.contributor.authorM. R. M., Rejab
dc.contributor.authorM. Y., Taib
dc.contributor.authorAbdullah, Ibrahim
dc.contributor.authorRosli, A. Bakar
dc.date.accessioned2010-08-23T09:10:41Z
dc.date.available2010-08-23T09:10:41Z
dc.date.issued2009-06-20
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/9027
dc.descriptionMUCEET 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.abstractMeasuring 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.isoenen_US
dc.publisherUniversiti Malaysia Pahang (UMP)en_US
dc.relation.ispartofseriesProceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCEET) 2009en_US
dc.subjectThermodynamics Ien_US
dc.subjectStatisticalen_US
dc.subjectGenetic algorithmsen_US
dc.subjectRadial Basis Function Network (RBFN)en_US
dc.subjectStudents -- Performanceen_US
dc.subjectMalaysian Technical Universities Conference on Engineering and Technology (MUCEET)en_US
dc.titleStudent performance analysis using artificial intelligent methoden_US
dc.typeWorking Paperen_US


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