TY  - JOUR
T1  - Differentiation of Agarwood Oil Quality Using Support Vector Machine (SVM)
AU - Jantan, Humuerah AU - Yassin, Ihsan M. AU - Zabidi, Azlee AU - Ismail, Nurlaila AU - Megat Ali, Megat Syahirul Amin 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 15
SP  - 3810
EP  - 3812
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.3810.3812
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.3810.3812
KW  - Agarwood oil
KW  -support vector machines
KW  -quality grading
KW  -commodity
KW  -implementation
KW  -outperforming
AB  - This research presents an Agarwood oil grading system using Support Vector Machine (SVM). Agarwood is grown in tropical parts of Asia (including Malaysia) and is a valuable international commodity. It is used primarily in fragrance and medicine. Data collected from 96 Agarwood oil samples of different qualities were used to train several SVMs with different Kernel functions. Implementation of the project was done using MATLAB v2010a. It was found that nonlinear Kernels were able to produce 100% accuracy, outperforming the linear Kernel (87.5% accuracy).
ER  -