ABDILLAH, MUHAMMAD and Saputra, Daniel and Kuncoro, Endo Argo (2019) PENENTUAN MUTU BUAH TOMAT (Solanum lycopersicum) MENGGUNAKAN PENGOLAHAN CITRA DIGITAL BERBASIS JARINGAN SYARAF TIRUAN DETERMINATION OF TOMATO (Solanum lycopersicum) QUALITY USING DIGITAL IMAGE PROCESSING BASED ON ARTIFICIAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.
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Abstract
The research objective was to determine the quality of tomatoes by nondestructive methods using a digital image processing program based on color analysis of tomatoes. This research used non-destructive image processing method to measure tomato quality using a digital image processing program based on RGB color parameter. Quality parameters were measured was brix and hardness (texture) of tomatoes. Image processing on 45 tomatoes to analysis of RGB color model and non-destructive measured data on 45 tomatoes were used to thedetermine quality value of tomato. Feed-forward backpropagation was used as learning algorithm for neural network models with logsig activation function to predicted brix and hardness using graphical user interface (GUI) Matlab R2017a that was developed, network architecture was formed by 3 input layers consisting of value red, green dan blue of tomato, 1 hidden layer (with 50 neurons for brix and 500 neurons for hardness) and layer of output is was tomato brix and hardness. The Program developed was able to analysis RGB color models whose values range from 0 and 1 as well digital numeric unit, image texture analysis and histogram graphs that were used as data from analyzed image information. Quality determination of tomatoes obtained from the equation of multi-regression brix y = ( -9.7873.10-5)X1 + (-3.8517.10-3)X2 + (-6.8991.10-3)X3 + 2.0397 and for hardness y =( -3.6069.10-2) X1 + (5.8101.10-2)X2 + (1.5947.10-1) X3 + 17.597, with X1 was the value Red color, X2 was the value Green color and X3 was the value Blue color, with units of color models in digital numbers.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | digital image processing, tomato, artificial neural network |
| Subjects: | S Agriculture > S Agriculture (General) > S671-760.5 Farm machinery and farm engineering |
| Divisions: | 05-Faculty of Agriculture > 41201-Agricultural Engineering (S1) |
| Depositing User: | Users 15 not found. |
| Date Deposited: | 17 Jul 2019 04:28 |
| Last Modified: | 27 Aug 2019 12:28 |
| URI: | http://repository.unsri.ac.id/id/eprint/353 |
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