Classification of Agarwood Oils Using K-NN K-Fold

摘要

Currently, the perfumery industries have been showing some interest in adding agarwood oils in their fragrance recipe because of its strong fixative effects and unique smell. From this highly interest of agarwood oil, there is a need for standardized agarwood oils grading system to be put into practice. In this study, selected agarwood-related chemicals compounds found in the GC-MS data analysis were used in order to group the samples into high and low. Electronic nose (EN) and Principal Component Analysis (PCA) were used in order to record sensors data and to select significant sensors. Lastly, from the classifier results, it was shown that the agarwood oils are successfully classified following two proposed groups high and low grades with high accuracy using k Nearest Neighbor k-fold (kNN k-fold).