Agarwood is a resin saturated heartwood producing its ownessential oil. This oil comprises of a complex mixture of chromone derivatives, oxygenated sesquiterpenes and sesquiterpene hydrocarbons. This mixture has a heavy woody scentand is one of the contributors to the Agarwood oil quality. In this paper, a study that focuses on the approach to select the substantial chemical compounds for Agarwood quality grading was carried out. GC-MS analysis was used to extract the chemical compounds from the Agarwood oil. The data were then pre-processed using techniques such as missing values ratio, natural logarithm and min. max. normalization. Next, synthetic data were generated using MUNGE to fulfil the passing condition of sampling adequacy test. To determine the substantial compounds, PCA and Pearson’s correlation were used. This approach was successful in determining three substantial compounds namely β-agarofuran, α-agarofuran and 10-epi-γ-eudesmol. These substantial chemical compounds will be used later to predict the quality of Agarwood oil
