The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method

Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were...

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Main Authors: M. M., Noor, K., Kadirgama, M. M., Rahman, M. R. M., Rejab, M. S. M., Sani, M. Y., Taib
Format: Conference or Workshop Item
Language:en
Published: 2009
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf
http://umpir.ump.edu.my/id/eprint/1428/
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_version_ 1831520988600205312
author M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
author_facet M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
author_sort M. M., Noor
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
description Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were randomly selected in faculty of mechanical engineering, University Malaysia Pahang. Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. Multilayer Perceptron Neural Network (MPNN) method was used to measure and predict the student’s performance. Result from the study shows that gender not significant role but entry results plays important role. Good entry results student normally maintain their performance throughout the study and become excellent graduates. MPNN is an important tool to study the different type of variables for student performance.
format Conference or Workshop Item
id my.ump.umpir.1428
institution Universiti Malaysia Pahang
language en
publishDate 2009
record_format eprints
spelling my.ump.umpir.14282018-01-23T02:00:09Z http://umpir.ump.edu.my/id/eprint/1428/ The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method M. M., Noor K., Kadirgama M. M., Rahman M. R. M., Rejab M. S. M., Sani M. Y., Taib LB2300 Higher Education Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were randomly selected in faculty of mechanical engineering, University Malaysia Pahang. Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. Multilayer Perceptron Neural Network (MPNN) method was used to measure and predict the student’s performance. Result from the study shows that gender not significant role but entry results plays important role. Good entry results student normally maintain their performance throughout the study and become excellent graduates. MPNN is an important tool to study the different type of variables for student performance. 2009 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf M. M., Noor and K., Kadirgama and M. M., Rahman and M. R. M., Rejab and M. S. M., Sani and M. Y., Taib (2009) The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method. In: Malaysian Technical Universities Conference on Engineering and Technology , 20-22 June 2009 , MS Garden Hotel, Kuantan, Pahang, Malaysia. . (Unpublished) (Unpublished)
spellingShingle LB2300 Higher Education
M. M., Noor
K., Kadirgama
M. M., Rahman
M. R. M., Rejab
M. S. M., Sani
M. Y., Taib
The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_full The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_fullStr The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_full_unstemmed The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_short The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method
title_sort entry qualifications and gender analysis of student performance by using artificial intelligent method
topic LB2300 Higher Education
url http://umpir.ump.edu.my/id/eprint/1428/1/2009_P_MUCEET09_Gender_M.M.Noor_K.Kadirgama-Conference-.pdf
http://umpir.ump.edu.my/id/eprint/1428/
url_provider http://umpir.ump.edu.my/