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...
| Κύριος συγγραφέας: | |
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| Μορφή: | Student Project |
| Γλώσσα: | English |
| Έκδοση: |
Faculty of Plantation and Agrotechnology
2014
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| Θέματα: | |
| Διαθέσιμο Online: | https://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf |
| _version_ | 1825734326205022208 |
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| author | Mohd Ripin, Mohd Syahir Alfathul Amin |
| author_facet | Mohd Ripin, Mohd Syahir Alfathul Amin |
| author_sort | Mohd Ripin, Mohd Syahir Alfathul Amin |
| collection | UITM |
| 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. |
| first_indexed | 2024-03-06T01:30:03Z |
| format | Student Project |
| id | oai:ir.uitm.edu.my:14678 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T01:30:03Z |
| publishDate | 2014 |
| publisher | Faculty of Plantation and Agrotechnology |
| record_format | dspace |
| spelling | oai:ir.uitm.edu.my:146782016-09-08T08:16:58Z https://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 https://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf Modelling the quality of harumanis mango (MA 128) grading using fuzzy logic system / Mohd Syahir Alfathul Amin Mohd Ripin. (2014) [Student Project] (Unpublished) |
| 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 |
| title | 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_short | 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 |
| topic | Fruit and fruit culture Marketing |
| url | https://ir.uitm.edu.my/id/eprint/14678/1/PPd_MOHD%20SYAHIR%20ALFTHUL%20AMIN%20MOHD%20RIPIN%20AT%2014_5.pdf |
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