Identifikasi Kematangan Buah Nanas Menggunakan Metode Jaringan Syaraf Tiruan

Bayu Fharadila, Feri Candra


Pineapple is a tropical fruit that is quite popular in Indonesia, especially in Riau Province. Pineapple can be processedto create derivativeproducts from pineapple. Therefore, the quality of pineapple maturity must be maintained. At present, the process of sorting the quality of pineapple is still done manually by humans, so errors can occur in the identification process. Therefore, this study provides a system that can classify the quality of pineapple by using Image Processing and Artificial Neural Networks.Pineapple images are captured by digital cameras and processed using Matlab. Digital Image Processing is used to extract pineapple colors. Artificial Neural Networks are used for classification of pineapple quality. This study uses 70 pineapples for training data and 30 pineapple to test data. The quality of pineapple is divided into 2 classes, raw and cooked pineapple. The used input parameters for Neural Networks are Red, Green, Blue. Accurasy obtained by this application is 100% so that this application is suitable to be used.
Keywords:, Digital Image Processing, Artificial Neural Networks.

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