Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani

Kaffir lime is originally from the Rutaceous family and is also known as 'Limau Purut'. These essential oils are extracted from leaves and peels. Nowadays, Kaffir lime oils are widely used in varieties of products and sold at erratic prices. However, the highest price of Kaffir lime oil do...

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Main Author:	Jak Jailani, Nor Syahira
Format:	Thesis
Language:	English
Published:	2022
Online Access:	https://ir.uitm.edu.my/id/eprint/83448/1/83448.pdf
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id	my-uitm-ir.83448
record_format	uketd_dc
spelling	my-uitm-ir.834482023-12-18T05:18:28Z Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani 2022 Jak Jailani, Nor Syahira Kaffir lime is originally from the Rutaceous family and is also known as 'Limau Purut'. These essential oils are extracted from leaves and peels. Nowadays, Kaffir lime oils are widely used in varieties of products and sold at erratic prices. However, the highest price of Kaffir lime oil does not guarantee the best quality oil of itself. The current method to rate the Kaffir lime oil by using human sensory such as nose and eyes provide confusion and inconsistent results. It can be concluded that sensory evaluation has the limitations such as easily fatigue and facing impossibilities to handle large samples at once. In order to solve this problem, many researchers discovered the chemical compound in Kaffir lime oil which can be used for oil quality grading to be more precisely. The objectives of this study are to identify the significant chemical compound in Kaffir lime oil based on Gas Chromatography-Mass Spectrometry (GC-MS) data and to develop a new model to classify the quality of Kaffir lime oils by applying the Non-linear Support Vector Machine (NSVM). 15 samples of Kaffir lime oil with different range of brands and prices from the highest to the lowest quality that were available in the market including the 11 samples of Kaffir lime oil from previous researchers were used in this study. Z-score technique is applied on GC-MS data to identify the significant compound in Kaffir lime oil. 2022 Thesis https://ir.uitm.edu.my/id/eprint/83448/ https://ir.uitm.edu.my/id/eprint/83448/1/83448.pdf text en public masters Universiti Teknologi MARA (UiTM) College of Engineering Muhammad, Zuraida
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Muhammad, Zuraida
description	Kaffir lime is originally from the Rutaceous family and is also known as 'Limau Purut'. These essential oils are extracted from leaves and peels. Nowadays, Kaffir lime oils are widely used in varieties of products and sold at erratic prices. However, the highest price of Kaffir lime oil does not guarantee the best quality oil of itself. The current method to rate the Kaffir lime oil by using human sensory such as nose and eyes provide confusion and inconsistent results. It can be concluded that sensory evaluation has the limitations such as easily fatigue and facing impossibilities to handle large samples at once. In order to solve this problem, many researchers discovered the chemical compound in Kaffir lime oil which can be used for oil quality grading to be more precisely. The objectives of this study are to identify the significant chemical compound in Kaffir lime oil based on Gas Chromatography-Mass Spectrometry (GC-MS) data and to develop a new model to classify the quality of Kaffir lime oils by applying the Non-linear Support Vector Machine (NSVM). 15 samples of Kaffir lime oil with different range of brands and prices from the highest to the lowest quality that were available in the market including the 11 samples of Kaffir lime oil from previous researchers were used in this study. Z-score technique is applied on GC-MS data to identify the significant compound in Kaffir lime oil.
format	Thesis
qualification_level	Master's degree
author	Jak Jailani, Nor Syahira
spellingShingle	Jak Jailani, Nor Syahira Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
author_facet	Jak Jailani, Nor Syahira
author_sort	Jak Jailani, Nor Syahira
title	Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
title_short	Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
title_full	Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
title_fullStr	Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
title_full_unstemmed	Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani
title_sort	intelligent grading of kaffir lime oil quality using non-linear support vector machine (nsvm) with rbf kernel / nor syahira jak jailani
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	College of Engineering
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/83448/1/83448.pdf
_version_	1794191972137697280

Intelligent grading of kaffir lime oil quality using non-linear support vector machine (NSVM) with RBF kernel / Nor Syahira Jak Jailani

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