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Image of PENENTUAN MUTU BUAH PEPAYA (CARICA PAPAYA L.) MENGGUNAKAN PENGOLAHAN CITRA (IMAGE PROCESSING) DAN JARINGAN SYARAF TIRUAN (JST)

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PENENTUAN MUTU BUAH PEPAYA (CARICA PAPAYA L.) MENGGUNAKAN PENGOLAHAN CITRA (IMAGE PROCESSING) DAN JARINGAN SYARAF TIRUAN (JST)

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The study aims to determine the quality of papaya fruit using image processing and artificial neural networks (JST) is to determine the quality of papaya fruit using image processing with artificial neural network method and simplify the papaya fruit selection process.The research was carried out from August 2022 to October 2022 at the Agricultural Product Technology laboratory, Faculty of Agriculture, Sriwijaya University. The factors that were analyzed using the Rancang Acak Kelompok Faktorial Method (RAKF) used were the super grade, A, B and treatments the mature, raw, ripe, and overripe levels of maturity. The study used four parameters of hardness, water content, total sugar and total acid Backpropagation artificial neural networks are used as learning algorithms with logsig activation functions for the prediction of hardness, moisture content, total sugar and total acid using the Matlab R2018a. Laboratory test results showed the parameters of hardness, water content, and total acid conducted a 5% BNJ further test against factor B, total sugar parameters conducted 5% BNJ further test on interaction. The development of the training artificial neural network model used 3 inputs (Red, Green, Blue) with the highest MSE value at the hardness parameter of 2,4904 x 103 . MSE value on parameters Water content 2,2807 x 10-4 , total sugar 3,1433 x 10-1 , total acid 2,3673 x 10-6 . Key words : artificial neural network, digital image processing, papaya


Availability
Inventory Code Barcode Call Number Location Status
2307000453T88010T880102023Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T880102023
Publisher
Inderalaya : Prodi Teknik Pertanian, Fakultas Pertanian Universitas Sriwijaya., 2023
Collation
xvi, 42 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
631.307
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Prodi Teknik Pertanian
Alat-alat, Mesin dan Perlengkapan Pertanian
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

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  • PENENTUAN MUTU BUAH PEPAYA (CARICA PAPAYA L.) MENGGUNAKAN PENGOLAHAN CITRA (IMAGE PROCESSING) DAN JARINGAN SYARAF TIRUAN (JST)
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