Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique

Recently, there has been growing interest in using agriculture food such as honey in food, beverage, pharmaceutical and medical industries. Specific honey type has their own usage and benefit. However, it is quite challenging task to classify different types of honey by simply using our naked eye.Th...

Full description

Bibliographic Details
Main Authors:	Nurdiyana, Zahed, M. S., Najib, Saiful Nizam, Tajuddin
Format:	Conference or Workshop Item
Language:	English
Published:	Universiti Malaysia Pahang 2016
Subjects:	Q Science (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/14769/ http://umpir.ump.edu.my/id/eprint/14769/ http://umpir.ump.edu.my/id/eprint/14769/1/Odour-Profile%20Classification%20of%20Gelam%2C%20Acacia.pdf

id	ump-14769
recordtype	eprints
spelling	ump-147692019-10-30T03:43:20Z http://umpir.ump.edu.my/id/eprint/14769/ Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin Q Science (General) TK Electrical engineering. Electronics Nuclear engineering Recently, there has been growing interest in using agriculture food such as honey in food, beverage, pharmaceutical and medical industries. Specific honey type has their own usage and benefit. However, it is quite challenging task to classify different types of honey by simply using our naked eye.The purpose of this study is to apply an electronic nose (E-nose) as an instrument to produce odor profile pattern for Gelam, Acacia and Tualang honey which are the common honey in Malaysia. Enose can produce signal for odor measurement in form of numeric resistance. Its measurement can pre-processed using normalization for standardized scale of unique features. Mean features is one of the unique features which extracted from the pre-processed data and statistical tool using boxplot representing the data pattern according to three types of honey (Gelam, Acacia and Tualang). Mean features that have been extracted were employed into K-Nearest Neighbors classifier as an input features. KNN performance have been evaluated using several splitting ratio. The results have shown that 100% rate of accuracy, sensitivity and specificity of classification from KNN using weigh (k=1), ratio 90:10 and Euclidean distance. It has been proven that the ability of KNN classifier as intelligent classification can be employed to classify different honey types from E-nose measured data. Universiti Malaysia Pahang 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14769/1/Odour-Profile%20Classification%20of%20Gelam%2C%20Acacia.pdf Nurdiyana, Zahed and M. S., Najib and Saiful Nizam, Tajuddin (2016) Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique. In: Proceedings of The National Conference for Postgraduate Research (NCON-PGR 2016), 24-25 September 2016 , Universiti Malaysia Pahang (UMP), Pekan, Pahang. pp. 404-412.. http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	Q Science (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	Q Science (General) TK Electrical engineering. Electronics Nuclear engineering Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
description	Recently, there has been growing interest in using agriculture food such as honey in food, beverage, pharmaceutical and medical industries. Specific honey type has their own usage and benefit. However, it is quite challenging task to classify different types of honey by simply using our naked eye.The purpose of this study is to apply an electronic nose (E-nose) as an instrument to produce odor profile pattern for Gelam, Acacia and Tualang honey which are the common honey in Malaysia. Enose can produce signal for odor measurement in form of numeric resistance. Its measurement can pre-processed using normalization for standardized scale of unique features. Mean features is one of the unique features which extracted from the pre-processed data and statistical tool using boxplot representing the data pattern according to three types of honey (Gelam, Acacia and Tualang). Mean features that have been extracted were employed into K-Nearest Neighbors classifier as an input features. KNN performance have been evaluated using several splitting ratio. The results have shown that 100% rate of accuracy, sensitivity and specificity of classification from KNN using weigh (k=1), ratio 90:10 and Euclidean distance. It has been proven that the ability of KNN classifier as intelligent classification can be employed to classify different honey types from E-nose measured data.
format	Conference or Workshop Item
author	Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin
author_facet	Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin
author_sort	Nurdiyana, Zahed
title	Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
title_short	Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
title_full	Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
title_fullStr	Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
title_full_unstemmed	Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique
title_sort	odour-profile classification of gelam, acacia and tualang honey based on k-nearest neighbors technique
publisher	Universiti Malaysia Pahang
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/14769/ http://umpir.ump.edu.my/id/eprint/14769/ http://umpir.ump.edu.my/id/eprint/14769/1/Odour-Profile%20Classification%20of%20Gelam%2C%20Acacia.pdf
first_indexed	2023-09-18T22:18:53Z
last_indexed	2023-09-18T22:18:53Z
_version_	1777415522723299328

Odour-Profile Classification of Gelam, Acacia and Tualang Honey based on K-Nearest Neighbors Technique

Similar Items