Agarwood Oil Quality Classifier Using Machine Learning

• Main Authors: M. A., Abas, N. S. A., Zubir, N., Ismail, N. A. M., Ali, Mohd Hezri Fazalul, Rahiman, Saiful Nizam, Tajuddin, M. N., Taib
• Format: Conference or Workshop Item
• Language: English
• Published: 2017
• Subjects: Q Science (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/18142/1/Agarwood%20Oil%20Quality%20Classifier%20Using%20Machine%20Learning.pdf; http://umpir.ump.edu.my/id/eprint/18142/

Agarwood Oil is known as one of the most expensive and precious oils being traded. It is widely used in traditional ceremonies, and religious prayers. It’s quality plays an important role on the market price that it can be traded. This paper proposes on a proper classification method of the agarwood oil quality using machine learning model k-nearest neighbour (k-NN). The chemical compounds of the agarwood oil from high and low quality are used to train and build the k-NN classifier model. Correlation-based feature selection was used to reduce the dimension of the data before it is being fed into the model. The results show a very high accuracy (100%) model trained and can be used to classify the agarwood oil quality accurately.