Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin

One of the factors that determining the market values of fruit is the quality. Most of the fruits for export markets are firstly sorted and graded according to the size and appearance of the fruits. The factors that caused the grading of fruits to varies because of lack of expenditure in purchasing...

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Main Author:	Mohd Ripin, Mohd Syahir Alfathul Amin
Format:	Student Project
Language:	English
Published:	Faculty of Plantation and Agrotechnology 2014
Subjects:	Fruit and fruit culture Marketing
Online Access:	http://ir.uitm.edu.my/id/eprint/14678/ http://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf

id	uitm-14678
recordtype	eprints
spelling	uitm-146782016-09-08T08:16:58Z http://ir.uitm.edu.my/id/eprint/14678/ Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin Mohd Ripin, Mohd Syahir Alfathul Amin Fruit and fruit culture Marketing One of the factors that determining the market values of fruit is the quality. Most of the fruits for export markets are firstly sorted and graded according to the size and appearance of the fruits. The factors that caused the grading of fruits to varies because of lack of expenditure in purchasing the grading machines, human error and well trained personnel. This research focus on the surface area of mango fruits, size of defect and number of defect presence on the mango skin. This study will grade of the Harumanis mango into various categories of classes such as grade A, B or C. This results which in to compare the accuracy of grading Harumanis fruit between manually system and Fuzzy Logic. The result of this study shows that modeling using Fuzzy logic will help to identify and forecast the input data to produce classification result which is of high accuracy. Through this process, the value of each element of input and output can be identify. These valuable data was inserted into Fuzzy Inference System (FIS) through Adaptive Neuro-Fuzzy Inference System (ANFIS). This method was the most suitable for forecasting the model data. The result shows that the classification result from the system achieved 85% accuracy. The grading system using these method can be applied to grade accurately varieties of fruits for domestic and export market. Faculty of Plantation and Agrotechnology 2014 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf Mohd Ripin, Mohd Syahir Alfathul Amin (2014) Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin. [Student Project] (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Fruit and fruit culture Marketing
spellingShingle	Fruit and fruit culture Marketing Mohd Ripin, Mohd Syahir Alfathul Amin Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
description	One of the factors that determining the market values of fruit is the quality. Most of the fruits for export markets are firstly sorted and graded according to the size and appearance of the fruits. The factors that caused the grading of fruits to varies because of lack of expenditure in purchasing the grading machines, human error and well trained personnel. This research focus on the surface area of mango fruits, size of defect and number of defect presence on the mango skin. This study will grade of the Harumanis mango into various categories of classes such as grade A, B or C. This results which in to compare the accuracy of grading Harumanis fruit between manually system and Fuzzy Logic. The result of this study shows that modeling using Fuzzy logic will help to identify and forecast the input data to produce classification result which is of high accuracy. Through this process, the value of each element of input and output can be identify. These valuable data was inserted into Fuzzy Inference System (FIS) through Adaptive Neuro-Fuzzy Inference System (ANFIS). This method was the most suitable for forecasting the model data. The result shows that the classification result from the system achieved 85% accuracy. The grading system using these method can be applied to grade accurately varieties of fruits for domestic and export market.
format	Student Project
author	Mohd Ripin, Mohd Syahir Alfathul Amin
author_facet	Mohd Ripin, Mohd Syahir Alfathul Amin
author_sort	Mohd Ripin, Mohd Syahir Alfathul Amin
title	Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
title_short	Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
title_full	Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
title_fullStr	Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
title_full_unstemmed	Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin
title_sort	modelling the quality of harumanis mango (ma 128) grading using fuzzy logic system / mohd syahir alfathul amin mohd ripin
publisher	Faculty of Plantation and Agrotechnology
publishDate	2014
url	http://ir.uitm.edu.my/id/eprint/14678/ http://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf
first_indexed	2023-09-18T22:52:10Z
last_indexed	2023-09-18T22:52:10Z
_version_	1777417616323772416

Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin

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