Preliminary Study on Classification of Cymbopogon Nardus Essential Oil using Support Vector Machine (SVM)

• Published in: 2020 11th IEEE Control and System Graduate Research Colloquium, ICSGRC 2020 - Proceedings
• Main Author: Zawani Mahabob N.; Mohd Yusoff Z.; Ismail N.; Nasir Taib M.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096925108&doi=10.1109%2fICSGRC49013.2020.9232661&partnerID=40&md5=b4ddb148ac22b06693132091ecd76211

Essential oils are concentrated oils produced by different parts of plants via distillation. Essential oils need to grade into high and low quality due to high quality essential oil being popular and commonly used in variety industries such as in cosmetics, perfumes and traditional medicines. On the previous researcher, many techniques regarding on method of extraction, chemical compounds of essential oil and the quality of essential oils have been presented. Currently, artificial neural network (ANN) is a popular method but this method has many local minima to be chosen as the best for a task. In the future study, Cymbopogon Nardus oil has been chosen for the proposed model due to its applications in mosquito repellent, medicine, food flavor and so on while SVM technique is chosen as classifier in C.Nardus oil. This paper presents an overview of essential oils and its previous analysis technique. Besides, the review on Support Vector Machine (SVM) is done to prove the technique is suitable for future research studies. © 2020 IEEE.