Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors

Honey authenticity refer to honey types is of great importance issue and interest in agriculture. In current research, several documents of specific types of honey have their own usage in medical field. However, it is quite challenging task to classify different types of honey by simply using our na...

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Main Authors:	Nurdiyana, Zahed, M. S., Najib, Saiful Nizam, Tajuddin
Format:	Article
Language:	English
Published:	Penerbit UMP 2018
Subjects:	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/1/Categorization%20of%20gelam%2C%20acacia%20and%20tualang%20honey%20odor-profile%20using%20k-nearest%20neighbors.pdf

id	ump-20870
recordtype	eprints
spelling	ump-208702019-10-30T03:42:26Z http://umpir.ump.edu.my/id/eprint/20870/ Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Honey authenticity refer to honey types is of great importance issue and interest in agriculture. In current research, several documents of specific types of honey have their own usage in medical field. However, it is quite challenging task to classify different types of honey by simply using our naked eye. This work demostrated a successful an electronic nose (E-nose) application as an instrument for identifying odor profile pattern of three common honey in Malaysia (Gelam, Acacia and Tualang honey). The applied E-nose has produced signal for odor measurement in form of numeric resistance (Ω). The data reading have been pre-processed using normalization technique for standardized scale of unique features. Mean features is extracted and boxplot used as the statistical tool to present the data pattern according to three types of honey. Mean features that have been extracted were employed into K-Nearest Neighbors classifier as an input features and evaluated using several splitting ratio. Excellent results were obtained by showing 100% rate of accuracy, sensitivity and specificity of classification from KNN using weigh (k=1), ratio 90:10 and Euclidean distance. The findings confirmed the ability of KNN classifier as intelligent classification to classify different honey types from E-nose calibration. Outperform of other classifier, KNN required less parameter optimization and achieved promising result. Penerbit UMP 2018 Article PeerReviewed text en http://umpir.ump.edu.my/id/eprint/20870/1/Categorization%20of%20gelam%2C%20acacia%20and%20tualang%20honey%20odor-profile%20using%20k-nearest%20neighbors.pdf Nurdiyana, Zahed and M. S., Najib and Saiful Nizam, Tajuddin (2018) Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors. International Journal of Software Engineering & Computer Sciences (IJSECS), 4 (1). pp. 15-28. ISSN 2289-8522 http://ijsecs.ump.edu.my/index.php/archive/17-v4/35-ijsecs-04-002 DOI: 10.15282/ijsecs.4.1.2018.2.0035
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
description	Honey authenticity refer to honey types is of great importance issue and interest in agriculture. In current research, several documents of specific types of honey have their own usage in medical field. However, it is quite challenging task to classify different types of honey by simply using our naked eye. This work demostrated a successful an electronic nose (E-nose) application as an instrument for identifying odor profile pattern of three common honey in Malaysia (Gelam, Acacia and Tualang honey). The applied E-nose has produced signal for odor measurement in form of numeric resistance (Ω). The data reading have been pre-processed using normalization technique for standardized scale of unique features. Mean features is extracted and boxplot used as the statistical tool to present the data pattern according to three types of honey. Mean features that have been extracted were employed into K-Nearest Neighbors classifier as an input features and evaluated using several splitting ratio. Excellent results were obtained by showing 100% rate of accuracy, sensitivity and specificity of classification from KNN using weigh (k=1), ratio 90:10 and Euclidean distance. The findings confirmed the ability of KNN classifier as intelligent classification to classify different honey types from E-nose calibration. Outperform of other classifier, KNN required less parameter optimization and achieved promising result.
format	Article
author	Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin
author_facet	Nurdiyana, Zahed M. S., Najib Saiful Nizam, Tajuddin
author_sort	Nurdiyana, Zahed
title	Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
title_short	Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
title_full	Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
title_fullStr	Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
title_full_unstemmed	Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors
title_sort	categorization of gelam, acacia and tualang honey odor-profile using k-nearest neighbors
publisher	Penerbit UMP
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/ http://umpir.ump.edu.my/id/eprint/20870/1/Categorization%20of%20gelam%2C%20acacia%20and%20tualang%20honey%20odor-profile%20using%20k-nearest%20neighbors.pdf
first_indexed	2023-09-18T22:30:21Z
last_indexed	2023-09-18T22:30:21Z
_version_	1777416244281999360

Categorization of Gelam, Acacia and Tualang Honey odor-profile using k-nearest neighbors

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