Mining Students' Data with Holland Model Using Neural Network and Logistic Regression

Education domain provides many interesting and challenging in data mining applications that potentially identified as a tool to help both educators and students, and improve the quality of education system. Nowadays, the impact of Minister of Education (MOE) regarding surplus graduates particularly...

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Main Author:	Noorlin, Mohd. Ali
Format:	Thesis
Language:	eng eng
Published:	2005
Subjects:	QA71-90 Instruments and machines QA76 Computer software
Online Access:	https://etd.uum.edu.my/1293/1/NOORLIN_BT._MOHD._ALI.pdf https://etd.uum.edu.my/1293/2/1.NOORLIN_BT._MOHD._ALI.pdf
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id	my-uum-etd.1293
record_format	uketd_dc
spelling	my-uum-etd.12932013-07-24T12:11:19Z Mining Students' Data with Holland Model Using Neural Network and Logistic Regression 2005-10-25 Noorlin, Mohd. Ali Faculty of Information Technology Faculty of Information Technology QA71-90 Instruments and machines QA76 Computer software Education domain provides many interesting and challenging in data mining applications that potentially identified as a tool to help both educators and students, and improve the quality of education system. Nowadays, the impact of Minister of Education (MOE) regarding surplus graduates particularly from public universities somehow had an impact on Universiti Utara Malaysia's (UUM) undergraduate intake. As a result, students who applied to undertake a program at Faculty of Information Technology and Faculty of Management Technology come from various background. Hence this study aims to get some insight into first year students undertaking undergraduate program such as Bachelor of Information Technology (BIT), Bachelor of Multimedia (BMM) and Bachelor in Management of Technology (BMoT) at Universiti Utara Malaysia. The Holland Personality Model was used to indicate the students' personality traits. The study concluded that BIT students are not from the Social type since none of the Social personality type is significant. Most of BIT students have Arts background, expect a few who have sat for Perkom (Perkomputeran) subject during the STPM examination. As for the Holland Model, It also appears that BIT students are more Artistic since 50% of the questions that measure the personality type is significant. In addition, the BIT students are Realistic (33.33%) and Investigative (33.33%) type. The results also reveal that the BIT students concluded as Artistic, Investigative and Realistic (AIR) in personality types that ar ein accordance to Holland personality theory, this finding were also supported by Hansen and Campbell (1985) that suggested that Investigative, Realistic and Artistic (IRA) should be the code for computer professionals. 2005-10 Thesis https://etd.uum.edu.my/1293/ https://etd.uum.edu.my/1293/1/NOORLIN_BT._MOHD._ALI.pdf application/pdf eng validuser https://etd.uum.edu.my/1293/2/1.NOORLIN_BT._MOHD._ALI.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA71-90 Instruments and machines QA76 Computer software
spellingShingle	QA71-90 Instruments and machines QA76 Computer software Noorlin, Mohd. Ali Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
description	Education domain provides many interesting and challenging in data mining applications that potentially identified as a tool to help both educators and students, and improve the quality of education system. Nowadays, the impact of Minister of Education (MOE) regarding surplus graduates particularly from public universities somehow had an impact on Universiti Utara Malaysia's (UUM) undergraduate intake. As a result, students who applied to undertake a program at Faculty of Information Technology and Faculty of Management Technology come from various background. Hence this study aims to get some insight into first year students undertaking undergraduate program such as Bachelor of Information Technology (BIT), Bachelor of Multimedia (BMM) and Bachelor in Management of Technology (BMoT) at Universiti Utara Malaysia. The Holland Personality Model was used to indicate the students' personality traits. The study concluded that BIT students are not from the Social type since none of the Social personality type is significant. Most of BIT students have Arts background, expect a few who have sat for Perkom (Perkomputeran) subject during the STPM examination. As for the Holland Model, It also appears that BIT students are more Artistic since 50% of the questions that measure the personality type is significant. In addition, the BIT students are Realistic (33.33%) and Investigative (33.33%) type. The results also reveal that the BIT students concluded as Artistic, Investigative and Realistic (AIR) in personality types that ar ein accordance to Holland personality theory, this finding were also supported by Hansen and Campbell (1985) that suggested that Investigative, Realistic and Artistic (IRA) should be the code for computer professionals.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Noorlin, Mohd. Ali
author_facet	Noorlin, Mohd. Ali
author_sort	Noorlin, Mohd. Ali
title	Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
title_short	Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
title_full	Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
title_fullStr	Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
title_full_unstemmed	Mining Students' Data with Holland Model Using Neural Network and Logistic Regression
title_sort	mining students' data with holland model using neural network and logistic regression
granting_institution	Universiti Utara Malaysia
granting_department	Faculty of Information Technology
publishDate	2005
url	https://etd.uum.edu.my/1293/1/NOORLIN_BT._MOHD._ALI.pdf https://etd.uum.edu.my/1293/2/1.NOORLIN_BT._MOHD._ALI.pdf
_version_	1747827114517725184

Mining Students' Data with Holland Model Using Neural Network and Logistic Regression

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