Classification of Shape Bean Coffee Using Convolutional Neural Network

P.P.P.A.N.W. Fikrul Ilmi R.H. Zer (Magister of Computer Science, Potensi Utama University)
Rika Rosnelly (Magister of Computer Science, Potensi Utama University)
Wanayumini Wanayumini (Magister of Computer Science, Potensi Utama University)

Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC)
Vol. 2 No. 1 (2023): Proceeding of International Conference on Information Science and Technology In

Deep Learning is a sub-field of Machine Learning in addressing the development of an image classification. This study uses a Deep Learning algorithm to classify the shape of coffee beans which consist of 4 types, namely defect, longberry, peaberry and premium. We use the Convolutional Neural Network to classify the shape of the coffee beans. This study combines the Convolutional Neural Network algorithm with Adam's optimization to get the best results. The research dataset uses training data of 4800 images and testing data of 1600 images with four classes. The results of this study get an accuracy result of 90,63%, a precision result of 88,23%, and a recall result of 95,74%. Based on the results obtained that the Convolutional Neural Network with Adam's optimization can be applied to the classification of coffee bean shapes with good results.