Classification Of Eligibility Consumption Of Manalagi Apple Fruit Varieties Using Backpropagation

This research aims to classify the quality of Manalagi apple fruit varieties prior to sorting them automatically. The sorting system used is still manually in fruit sorting with the help of human labor that takes a long time. The sorting process is slow therefore the sorted result is low in number and inconsistent in quality. The parameters used in the Manalagi apple classification are based on the skin color of the fruit. The color of the fruit skin will be taken color features with average RGB. In this study, the classification system is automatically developed for the Manalagi apple fruit with the extraction of the average RGB color feature with the Backpropagation algorithm. The purpose of the developed system is to distinguish the Manalagi apple fruit of worth consumption and not worth the consumption. The fruit classification is based on the average RGB color composition of the fruit skin. Systems developed using image processing such as image segmentation, color feature extraction with average RGB models and fruit quality classification decisions with the Backpropagation algorithm. The developed system can take the decision automatically fruit worth consumption and not worth the consumption with an accuracy rate of 90%.