Indonesian Journal of Electrical Engineering and Computer Science Vol. 27, No. 3, September 2022, pp. 1358~1365 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v27.i3.pp1358-1365  1358 Journal homepage: http://ijeecs.iaescore.com A preliminary study on the intelligent model of k-nearest neighbor for agarwood oil quality grading Siti Mariatul Hazwa Mohd Huzir 1 , Noratikah Zawani Mahabob 2 , Aqib Fawwaz Mohd Amidon 2 , Nurlaila Ismail 2 , Zakiah Mohd Yusoff 1 , Mohd Nasir Taib 3 1 Department of System, School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Masai, Malaysia 2 Department of System, School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam, Malaysia 3 Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA, Shah Alam, Malaysia Article Info ABSTRACT Article history: Received Feb 25, 2021 Revised Jun 14, 2022 Accepted Jul 14, 2022 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. Keywords: Agarwood oil quality Essential oils Euclidean distance Extraction K-nearest neighbor This is an open access article under the CC BY-SA license. Corresponding Author: Nurlaila Ismail School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA Shah Alam, Selangor, Malaysia Email: nurlaila0583@uitm.edu.my 1. INTRODUCTION Essential oil is a commodity that captures volatile aromatic essences extracted from different parts of the trees. Based on the Medical News Today, essential oil therapy is also one of the alternative medicine for psychological treatment. It is commonly used in the practice of aromatherapy [1], [2]. Recently, it is valued in many cultures where it is being used to treat various illnesses, perfumery and incense for religious and spiritual ceremonies purposes [3]-[5]. Currently, essential oil quality was measured and graded manually using sensory evaluation based on physical properties. Based on human perception and experience, an essential oil with the greatest grade has a lot of resin, dark oil color, strong odor and long-lasting aroma [3], [6], [7]. However, the sensory evaluation method is somehow inaccurate since different people may come with different perceptions and decisions about the technique. There is no guarantee that grading using human sensory evaluation can secure the purity or quality of the essential oils. Human trained grader technique has a significant disadvantage in terms of objectivity and repeatability due to the continuous process when deal with a bulk of samples at once, contribute to the high labor-intensive process and time-consuming [8]-[10]. As a result, several methods have been proposed and implemented to verify essential oil quality using intelligent techniques [8], [9], [11]-[17]. Agarwood oil is commonly used for medical purposes, ritual and fragrances. In today’s modern society, agarwood oil become a hot topic among customers due to the strong odor, high content of resins and