Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar

Choosing a school for the secondary students is not a simple task nowadays since there are many factors needed to be considered by parents. These might be an overhead to the parents to filter each school and try to sort it out based on their requirements. Therefore, a predictive model which is a qua...

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Main Author:	Mohamad Hafizi Masdar
Format:	Thesis
Language:	English
Published:	2017
Online Access:	http://ir.uitm.edu.my/id/eprint/18157/ http://ir.uitm.edu.my/id/eprint/18157/2/TD_MOHAMAD%20HAFIZI%20MASDAR%20CS%2017_5.pdf

id	uitm-18157
recordtype	eprints
spelling	uitm-181572019-02-27T07:51:36Z http://ir.uitm.edu.my/id/eprint/18157/ Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar Mohamad Hafizi Masdar Choosing a school for the secondary students is not a simple task nowadays since there are many factors needed to be considered by parents. These might be an overhead to the parents to filter each school and try to sort it out based on their requirements. Therefore, a predictive model which is a quantitative research that implemented artificial intelligence (AI) strategy using Naïve Bayes (NB) technique been applied in order to predict the chosen secondary school in Gombak based on parents’ preferences. Through six different independent variables (IV) namely distance of home from school (DSH), sibling enrolment in the same school (SE), highest parent’s level of education (PLE), household income (HI), employment status (ES) and race, 64 prediction models were produced and tested. Among all these models, the highest accuracy detected was the combination of four IVs which are DSH, PLE, ES and race, that resulted more than 55% of accuracy. This finding then implemented into a system which is Prediction of Secondary Public School System (PSPSS) to help parents making school selection easier since parents’ concerns are taken into consideration. NB provided a new way of solving a problem in determining the vital factors for making a school choice. Since this is the preliminary and exploratory study, the highlighted achievement is not the accuracy percentage of the prediction, but a new angle on the ability of how AI can solve the problem within the domain of this study. This finding can be further improved by using the same technique which is NB through modification of IV used and the number of data collected. Other AI techniques such as support vector machine (SVM), multiple linear regression (MLR) and artificial neural network (ANN) also can be used to compare with the current NB as well as an enhancement to readily available findings. This study also may be broadened to other regions or states to help more parents making school selection easier. 2017 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/18157/2/TD_MOHAMAD%20HAFIZI%20MASDAR%20CS%2017_5.pdf Mohamad Hafizi Masdar (2017) Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar. Degree thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
description	Choosing a school for the secondary students is not a simple task nowadays since there are many factors needed to be considered by parents. These might be an overhead to the parents to filter each school and try to sort it out based on their requirements. Therefore, a predictive model which is a quantitative research that implemented artificial intelligence (AI) strategy using Naïve Bayes (NB) technique been applied in order to predict the chosen secondary school in Gombak based on parents’ preferences. Through six different independent variables (IV) namely distance of home from school (DSH), sibling enrolment in the same school (SE), highest parent’s level of education (PLE), household income (HI), employment status (ES) and race, 64 prediction models were produced and tested. Among all these models, the highest accuracy detected was the combination of four IVs which are DSH, PLE, ES and race, that resulted more than 55% of accuracy. This finding then implemented into a system which is Prediction of Secondary Public School System (PSPSS) to help parents making school selection easier since parents’ concerns are taken into consideration. NB provided a new way of solving a problem in determining the vital factors for making a school choice. Since this is the preliminary and exploratory study, the highlighted achievement is not the accuracy percentage of the prediction, but a new angle on the ability of how AI can solve the problem within the domain of this study. This finding can be further improved by using the same technique which is NB through modification of IV used and the number of data collected. Other AI techniques such as support vector machine (SVM), multiple linear regression (MLR) and artificial neural network (ANN) also can be used to compare with the current NB as well as an enhancement to readily available findings. This study also may be broadened to other regions or states to help more parents making school selection easier.
format	Thesis
author	Mohamad Hafizi Masdar
spellingShingle	Mohamad Hafizi Masdar Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
author_facet	Mohamad Hafizi Masdar
author_sort	Mohamad Hafizi Masdar
title	Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
title_short	Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
title_full	Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
title_fullStr	Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
title_full_unstemmed	Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar
title_sort	prediction of secondary public school selection based on parents’ preferences using naïve bayes / mohamad hafizi masdar
publishDate	2017
url	http://ir.uitm.edu.my/id/eprint/18157/ http://ir.uitm.edu.my/id/eprint/18157/2/TD_MOHAMAD%20HAFIZI%20MASDAR%20CS%2017_5.pdf
first_indexed	2023-09-18T22:59:53Z
last_indexed	2023-09-18T22:59:53Z
_version_	1777418102545317888

Prediction of secondary public school selection based on parents’ preferences using naïve bayes / Mohamad Hafizi Masdar

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