Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan

Two types of lipid that can be related which are fat and fat-free mass. There are several methods to calculate body fat percentage like numerous formula equations, artificial neural network (ANN) technique and body fat callipers tool by using independent variables (IV) such as gender, age and BMI. A...

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Main Author:	Mazalan, Nurfarah Mazarina
Format:	Thesis
Language:	English
Published:	2017
Online Access:	https://ir.uitm.edu.my/id/eprint/18243/2/TD_NURFARAH%20MAZARINA%20MAZALAN%20CS%2017_5.pdf
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id	my-uitm-ir.18243
record_format	uketd_dc
spelling	my-uitm-ir.182432019-02-28T02:35:48Z Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan 2017 Mazalan, Nurfarah Mazarina Two types of lipid that can be related which are fat and fat-free mass. There are several methods to calculate body fat percentage like numerous formula equations, artificial neural network (ANN) technique and body fat callipers tool by using independent variables (IV) such as gender, age and BMI. All techniques have quite similar and applicable to use since the system is easy to use, require low budget and no surgery involved to predict body fat percentage. However, the performance of existing techniques was unclear due its results. Thus, this project presents a new system solver via prediction model to repeat the research with brand new approach which is Naïve Bayes (NB) in predicting body fat status. The inputs as IV that involves in NB are gender, age and BMI for the basic fat prediction and daily routines’ frequencies for the new IV for the new fat prediction model. Throughout the 63 models of testing done, the results gave an average of 70% accuracy from 225 data learnt. Moreover, all the functionality testing results are successfully pass proving the system is well functioned. This research may get a chance to extend by changing the IV, increasing the amount of data set or using other AI techniques to get higher accuracy. 2017 Thesis https://ir.uitm.edu.my/id/eprint/18243/ https://ir.uitm.edu.my/id/eprint/18243/2/TD_NURFARAH%20MAZARINA%20MAZALAN%20CS%2017_5.pdf text en public dphil degree Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
description	Two types of lipid that can be related which are fat and fat-free mass. There are several methods to calculate body fat percentage like numerous formula equations, artificial neural network (ANN) technique and body fat callipers tool by using independent variables (IV) such as gender, age and BMI. All techniques have quite similar and applicable to use since the system is easy to use, require low budget and no surgery involved to predict body fat percentage. However, the performance of existing techniques was unclear due its results. Thus, this project presents a new system solver via prediction model to repeat the research with brand new approach which is Naïve Bayes (NB) in predicting body fat status. The inputs as IV that involves in NB are gender, age and BMI for the basic fat prediction and daily routines’ frequencies for the new IV for the new fat prediction model. Throughout the 63 models of testing done, the results gave an average of 70% accuracy from 225 data learnt. Moreover, all the functionality testing results are successfully pass proving the system is well functioned. This research may get a chance to extend by changing the IV, increasing the amount of data set or using other AI techniques to get higher accuracy.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Bachelor degree
author	Mazalan, Nurfarah Mazarina
spellingShingle	Mazalan, Nurfarah Mazarina Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
author_facet	Mazalan, Nurfarah Mazarina
author_sort	Mazalan, Nurfarah Mazarina
title	Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
title_short	Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
title_full	Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
title_fullStr	Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
title_full_unstemmed	Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan
title_sort	prediction of body fat status by using naïve bayes technique among university students / nurfarah mazarina mazalan
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2017
url	https://ir.uitm.edu.my/id/eprint/18243/2/TD_NURFARAH%20MAZARINA%20MAZALAN%20CS%2017_5.pdf
_version_	1783733641408413696

Prediction of body fat status by using naïve bayes technique among university students / Nurfarah Mazarina Mazalan

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