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With the forestry and logging activities contributing to 5.6% of the agricultural sector in Malaysia's 2018 GDP growth, this had thus implied the forest as having a significant role in national growth and the critical need of a precise tree volume estimation. Although regression has been the most common method used for this form of estimation, the expansion of information technology had, however, led to the use of a machine learning technique that is capable of overcoming the issues posed by the regression analysis. In this paper, the estimation of the tree volume was not only conducted via the regression method but had also involved the use of two machine learning techniques, namely the artificial neural network (ANN) and that of the epsilon-Support Vector Regression (ε-SVR). By comparing the root mean square error (RMSE) and standard deviation (SD) values from each of the volume model that had been …