Indonesian Journal of Electrical Engineering and Computer Science
Vol 27, No 3: September 2022

A Ppreliminary study on the intelligent model of k-nearest neighbor for agarwood oil quality grading

Siti Mariatul Hazwa Mohd Huzir (Universiti Teknologi MARA)
Noratikah Zawani Mahabob (Universiti Teknologi MARA)
Aqib Fawwaz Mohd Amidon (Universiti Teknologi MARA)
Nurlaila Ismail (Universiti Teknologi MARA)
Zakiah Mohd Yusoff (Universiti Teknologi MARA)
Mohd Nasir Taib (Universiti Teknologi MARA)



Article Info

Publish Date
01 Sep 2022

Abstract

Essential oils extracted from trees has various usages like perfumes, incense, aromatherapy and traditional medicine which increase their popularity in global market. In Malaysia, the recognition system for identifying the essential oil quality still does not reach its standard since mostly graded by using human sensory evaluation. However, previous researchers discovered new modern techniques to present the quality of essential oils by analyse the chemical compounds. Agarwood essential oil had been chosen for the proposed integrated intelligent models with the implementation of k-nearest neighbor (k-NN) due to the high demand and an expensive natural raw world resource. k-NN with Euclidean distance metrics had better performance in terms of its confusion matrix, sensitivity, precision accuracy and specificity. This paper presents an overview of essential oils as well as their previous analysis technique. The review on k-NN is done to prove the technique is compatible for future research studies based on its performance.

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