Application Of The Backpropagation Method For Digital Image Feature Extraction On Coffee Fruit Classification - Riduan Syahri; Desi Puspita (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING, 2023)
The background of this research is that the process of classifying the types of coffee beans is still carried out conventionally and has not been computerized, that is, the classification of coffee beans is still based on experience, color and shape of the coffee beans. Of course, this takes a long time and errors often occur, so this research can help classify coffee cherries using the Backpropagation method quickly. The purpose of this study was to produce a system for applying the backpropagation method for extracting digital image features in the classification of coffee cherries, a system built using MATLAB software. In the results of the coffee fruit classification program with the Backpropagation algorithm that is matched in excel, results are obtained for an accuracy of 72% for 100 training data and results for an accuracy of 85% for 10 test data for manual calculations, results are obtained from the Performance Model Using the Confusion Matrix in training data obtained an accuracy of 72% and testing 85% of each of the 2 different types of coffee cherries.