Classification of Arabica and Robusta coffee using electronic nose

Abstract

The ability of nose as the sense of smell, causing high sensitivity to the aroma of coffee. The electronic nose can be applied to recognize the aroma of coffee as an objective measure of coffee gas. The detection of Arabica and Robusta coffee was diluted for 20 minutes and resulted in 288 gas data. From the data displayed on the Arduino produces different signal values. From the results of sensor data displayed on the Arduino will be made aroma classification based signal data. Classification of Arabica coffee aroma and Robusta coffee aroma is done with Support Vector Machine (SVM) and Perceptron method. Accuracy results obtained with the SVM method is 71% and Perceptron 57%. Based on the accuracy value obtained, SVM method can recognize Arabica Coffee and Robusta with better results.