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PENENTUAN MUTU BUAH PEPAYA (CARICA PAPAYA L.) MENGGUNAKAN PENGOLAHAN CITRA (IMAGE PROCESSING) DAN JARINGAN SYARAF TIRUAN (JST)
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
Inventory Code | Barcode | Call Number | Location | Status |
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2307000453 | T88010 | T880102023 | Central Library (Referens) | Available but not for loan - Not for Loan |
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