Coffee Type Classification Using Backpropagation Artificial Neural Network - Adytia, Pitrasacha; Wahyuni, Wahyuni; Asmaramany, Dimas; Sussolaikah, Kelik (Indonesian Journal of Artificial Intelligence and Data Mining, 2024)
Coffee has several types including robusta coffee, arabica coffee and luwak coffee. Each coffee has certain characteristics of color, texture, aroma and also the quality of the taste. Coffee counterfeiting is also common. This coffee counterfeiting usually uses materials such as corn, wheat, soybeans, husks, sticks and robusta coffee beans. So that a model is needed to be able to classify the type of coffee. This research uses artificial neural network machine learning algorithms to identify and classify coffee. Quality training and testing data is needed in this method because it will affect the final results. Initial data is collected via e-nose, with this equipment data on changes in electrical voltage will be obtained from 4 sensors, namely MQ-2, MQ-3, MQ-7 and MQ-135. These 4 features will be used in the classification process. With 900 sets of training data, the test results show that the neural network is able to provide correct classification 99% of the 3 sets of testing data. The results of training and testing show that the neural network formed can identify and distinguish coffee types with good results.