Neural network and regression models for matriculation college

Data mining is a popular technique to find hidden in formation in database. A lot of studies have been conducted to show that data mining technique is a powerful tool that is capable to provide highly targeted information to support decision making and forecasting for business, science, health, educ...

Full description

Bibliographic Details
Main Authors: Razali, Shahirawaty, Siraj, Fadzilah, Yusoff, Nooraini
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/9588/1/sh.pdf
_version_ 1803625869441236992
author Razali, Shahirawaty
Siraj, Fadzilah
Yusoff, Nooraini
author_facet Razali, Shahirawaty
Siraj, Fadzilah
Yusoff, Nooraini
author_sort Razali, Shahirawaty
collection UUM
description Data mining is a popular technique to find hidden in formation in database. A lot of studies have been conducted to show that data mining technique is a powerful tool that is capable to provide highly targeted information to support decision making and forecasting for business, science, health, education, industry and others.In education sector, data mining techniques is normally used to predict student’s performance in certain courses, to forecast the lecturers performance at the university and others. Indirectly, these techniques contribute towards a better quality education management, as well as to assist the education institution managing the administrative tasks effectively. This study aims to develop prediction models for determining the program undertaken at Matriculation College based on the student’s background, academic achievement as well as personality traits.To accomplish this, NN model known as multilayer perceptron with back propagation learning and regression model were employed. The findings show that Neural Network has more accuracy percentage than Logistic Regression.It also presents the existing relationship between students‘ achievements, personality traits and course undertaken.
first_indexed 2024-07-04T05:41:08Z
format Conference or Workshop Item
id uum-9588
institution Universiti Utara Malaysia
language English
last_indexed 2024-07-04T05:41:08Z
publishDate 2006
record_format dspace
spelling uum-95882014-03-10T07:10:58Z https://repo.uum.edu.my/id/eprint/9588/ Neural network and regression models for matriculation college Razali, Shahirawaty Siraj, Fadzilah Yusoff, Nooraini QA75 Electronic computers. Computer science Data mining is a popular technique to find hidden in formation in database. A lot of studies have been conducted to show that data mining technique is a powerful tool that is capable to provide highly targeted information to support decision making and forecasting for business, science, health, education, industry and others.In education sector, data mining techniques is normally used to predict student’s performance in certain courses, to forecast the lecturers performance at the university and others. Indirectly, these techniques contribute towards a better quality education management, as well as to assist the education institution managing the administrative tasks effectively. This study aims to develop prediction models for determining the program undertaken at Matriculation College based on the student’s background, academic achievement as well as personality traits.To accomplish this, NN model known as multilayer perceptron with back propagation learning and regression model were employed. The findings show that Neural Network has more accuracy percentage than Logistic Regression.It also presents the existing relationship between students‘ achievements, personality traits and course undertaken. 2006 Conference or Workshop Item NonPeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/9588/1/sh.pdf Razali, Shahirawaty and Siraj, Fadzilah and Yusoff, Nooraini (2006) Neural network and regression models for matriculation college. In: Master Projects Seminar, 2006, Fakulti Teknologi Maklumat, Universiti Utara Malaysia. (Unpublished)
spellingShingle QA75 Electronic computers. Computer science
Razali, Shahirawaty
Siraj, Fadzilah
Yusoff, Nooraini
Neural network and regression models for matriculation college
title Neural network and regression models for matriculation college
title_full Neural network and regression models for matriculation college
title_fullStr Neural network and regression models for matriculation college
title_full_unstemmed Neural network and regression models for matriculation college
title_short Neural network and regression models for matriculation college
title_sort neural network and regression models for matriculation college
topic QA75 Electronic computers. Computer science
url https://repo.uum.edu.my/id/eprint/9588/1/sh.pdf
work_keys_str_mv AT razalishahirawaty neuralnetworkandregressionmodelsformatriculationcollege
AT sirajfadzilah neuralnetworkandregressionmodelsformatriculationcollege
AT yusoffnooraini neuralnetworkandregressionmodelsformatriculationcollege