Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation
DOI:
https://doi.org/10.29408/jit.v2i1.976Keywords:
Image processing, Backpropagation Neural Network, GLCM, Extraction Characteristics, Cucumber maturityAbstract
Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.
DOI : 10.29408/jit.v2i1.976
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