Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital
Fruits are one of important agricultural commodities in Indonesia. Banana is one of fruits commodities with high demand because it has a lot of benefits. Community needs for domestic and non domestic market on bananas also followed with guaranteed qualities. With many varieties of banana, Pisang Mas...
| Main Authors: | , |
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2014
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| author | , DIDI WIDJANARKO , Dr. Atris Suyantohadi, STP, MT. |
| author_facet | , DIDI WIDJANARKO , Dr. Atris Suyantohadi, STP, MT. |
| author_sort | , DIDI WIDJANARKO |
| collection | UGM |
| description | Fruits are one of important agricultural commodities in Indonesia. Banana
is one of fruits commodities with high demand because it has a lot of benefits.
Community needs for domestic and non domestic market on bananas also
followed with guaranteed qualities. With many varieties of banana, Pisang Mas is
sold quite high on retail level compared another bananas variety. Maturity level of
banana is one of the determining factors for quality. Sorting process on Pisang
Mas based on color grade usually depend on human�s perception of color images
composition factor owned by the fruit. The development of the image processing
system, which is combined with a method to apply the artificial neural network
(ANN), enabled for the identification of the level of maturity of Pisang Mas
according to grade more accurately and quickly.
In this study igital image processing refers to two-dimensional images
processing using a computer. ANN is a computational system which the
architecture and operation system inspired by the knowledge about the biological
neuron cells in brain. Pisang Mas are varieties from Kebun Plasma Nutfah Pisang
Yogyakarta. Number of sample is 84 bananas which divided into 2 groups, 56
bananas ( 224 images) as training data and 28 bananas ( 112 images) to testing the
network. Image capturing of each sample conducted on each of four sides. The
parameters used as input to the ANN is mean Red, mean Green, homogeneity and
contrast.
The results in this study show that, with combining image processing and
artificial neural network method, maturity level identification of Pisang Mas
veriety based on USDA standard (green, light green, yellowish green, greenish
yellow, yellow with green tips, yellow and yellow flecked with brown) can be
successfully done. ANN architecture consisted of four cells |
| first_indexed | 2024-03-13T23:30:29Z |
| format | Thesis |
| id | oai:generic.eprints.org:130793 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:30:29Z |
| publishDate | 2014 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1307932016-03-04T07:54:52Z https://repository.ugm.ac.id/130793/ Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital , DIDI WIDJANARKO , Dr. Atris Suyantohadi, STP, MT. ETD Fruits are one of important agricultural commodities in Indonesia. Banana is one of fruits commodities with high demand because it has a lot of benefits. Community needs for domestic and non domestic market on bananas also followed with guaranteed qualities. With many varieties of banana, Pisang Mas is sold quite high on retail level compared another bananas variety. Maturity level of banana is one of the determining factors for quality. Sorting process on Pisang Mas based on color grade usually depend on human�s perception of color images composition factor owned by the fruit. The development of the image processing system, which is combined with a method to apply the artificial neural network (ANN), enabled for the identification of the level of maturity of Pisang Mas according to grade more accurately and quickly. In this study igital image processing refers to two-dimensional images processing using a computer. ANN is a computational system which the architecture and operation system inspired by the knowledge about the biological neuron cells in brain. Pisang Mas are varieties from Kebun Plasma Nutfah Pisang Yogyakarta. Number of sample is 84 bananas which divided into 2 groups, 56 bananas ( 224 images) as training data and 28 bananas ( 112 images) to testing the network. Image capturing of each sample conducted on each of four sides. The parameters used as input to the ANN is mean Red, mean Green, homogeneity and contrast. The results in this study show that, with combining image processing and artificial neural network method, maturity level identification of Pisang Mas veriety based on USDA standard (green, light green, yellowish green, greenish yellow, yellow with green tips, yellow and yellow flecked with brown) can be successfully done. ANN architecture consisted of four cells [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , DIDI WIDJANARKO and , Dr. Atris Suyantohadi, STP, MT. (2014) Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=71225 |
| spellingShingle | ETD , DIDI WIDJANARKO , Dr. Atris Suyantohadi, STP, MT. Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title | Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title_full | Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title_fullStr | Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title_full_unstemmed | Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title_short | Program Aplikasi Untuk Identifikasi Tingkat Kematangan Buah Pisang Mas (Musa Paradisiaca l) Berdasarkan Parameter Citra dengan Teknologi Pengolahan Citra Digital |
| title_sort | program aplikasi untuk identifikasi tingkat kematangan buah pisang mas musa paradisiaca l berdasarkan parameter citra dengan teknologi pengolahan citra digital |
| topic | ETD |
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