Characterization and Classification of Coffee Bean Types using Support Vector Machine

Abstract

This study describes the characterization and classification of coffee bean types using the support vector machine. The benefits of this study are to provide knowledge that shows that there is a feasible way of classifying and characterizing coffee bean types based on its aroma using support vector machine and an electronic nose system. The results of the study was a success, the researchers were able to successfully process the data on a laptop using Support Vector Machine and display the proper coffee bean type on the LCD display on the electronic nose system. Looking at the results of the study, The researchers were able to train their machine-learning algorithm to be able to yield an accuracy of at least 70%. They, therefore, concluded that the constructed electronic nose is capable of accurately identifying coffee bean types based on its aroma using Support Vector Machine, this accuracy in results can be of use to future researchers who wish to use this paper for scientific references.