PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN
the Bananas does not only supply the domestic market, but also the international market. Therefore, the quality of banana fruit should be maintained. Currently, quality sorting process of bananas are still done manually by humans, consequently result is not good. So we need a system that can classif...
| Main Authors: | , |
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2013
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| _version_ | 1826047403717820416 |
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| author | , YANUAR PUTU WIHARJA , Dr. Agus Harjoko |
| author_facet | , YANUAR PUTU WIHARJA , Dr. Agus Harjoko |
| author_sort | , YANUAR PUTU WIHARJA |
| collection | UGM |
| description | the
Bananas does not only supply the domestic market, but also the international
market. Therefore, the quality of banana fruit should be maintained. Currently,
quality sorting process of bananas are still done manually by humans, consequently
result is not good. So we need a system that can classify quality of bananas by
using image processing and artificial neural network.
10
Banana image captured by a digital camera and processed using Matlab.
Digital image processing is used to extract color and texture features of banana.
While artificial neural networks used for classification of the quality of bananas.
This study uses 125 bananas for training data and 100 bananas for testing data.
Quality of bananas are divided into 5 classes, Super, class A, class B, external
quality I and external quality II.
Input parameters used for the neural network are area defects, red, green, blue,
energy, homogeneity, and contrast. Best configuration of backpropagation network
model for a classification system of banana quality is the learning rate of 0.3 and
neurons in the hidden layer. With the best configuration, the system is able to
classify the quality of banana fruit with 94% accuracy rate from 100 bananas test
data. |
| first_indexed | 2024-03-13T23:10:14Z |
| format | Thesis |
| id | oai:generic.eprints.org:125333 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:10:14Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1253332016-03-04T08:44:33Z https://repository.ugm.ac.id/125333/ PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN , YANUAR PUTU WIHARJA , Dr. Agus Harjoko ETD the Bananas does not only supply the domestic market, but also the international market. Therefore, the quality of banana fruit should be maintained. Currently, quality sorting process of bananas are still done manually by humans, consequently result is not good. So we need a system that can classify quality of bananas by using image processing and artificial neural network. 10 Banana image captured by a digital camera and processed using Matlab. Digital image processing is used to extract color and texture features of banana. While artificial neural networks used for classification of the quality of bananas. This study uses 125 bananas for training data and 100 bananas for testing data. Quality of bananas are divided into 5 classes, Super, class A, class B, external quality I and external quality II. Input parameters used for the neural network are area defects, red, green, blue, energy, homogeneity, and contrast. Best configuration of backpropagation network model for a classification system of banana quality is the learning rate of 0.3 and neurons in the hidden layer. With the best configuration, the system is able to classify the quality of banana fruit with 94% accuracy rate from 100 bananas test data. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , YANUAR PUTU WIHARJA and , Dr. Agus Harjoko (2013) PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=65500 |
| spellingShingle | ETD , YANUAR PUTU WIHARJA , Dr. Agus Harjoko PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title | PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title_full | PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title_fullStr | PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title_full_unstemmed | PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title_short | PEMROSESAN CITRA DIGITAL UNTUK KLASIFIKASI MUTU BUAH PISANG MENGGUNAKAN JARINGAN SARAF TIRUAN |
| title_sort | pemrosesan citra digital untuk klasifikasi mutu buah pisang menggunakan jaringan saraf tiruan |
| topic | ETD |
| work_keys_str_mv | AT yanuarputuwiharja pemrosesancitradigitaluntukklasifikasimutubuahpisangmenggunakanjaringansaraftiruan AT dragusharjoko pemrosesancitradigitaluntukklasifikasimutubuahpisangmenggunakanjaringansaraftiruan |