E. longifolia is attracting interest due to its pharmacological properties and pro-vitality effects. In this study, an online SPE-LC approach using polystyrene divinyl benzene (PSDVB) and C18 columns was developed in obtaining chromatographic fingerprints of E. longifolia. E. longifolia root samples were extracted using pressurized liquid extraction (PLE) technique prior to online SPE-LC. The effects of mobile phase compositions and column switching time on the chromatographic fingerprint were optimized. Validation of the developed method was studied based on eurycomanone. Linearity was in the range of 5 to 50 µg∙mL−1 (r2 = 0.997) with 3.2% relative standard deviation of peak area. The developed method was used to analyze 14 E. longifolia root samples and 10 products (capsules). Selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) were applied to the fingerprint datasets of 37 selected peaks to evaluate the ability of the chromatographic fingerprint in classifying quality of E. longifolia. Three groups were obtained using CA. DA yielded 100% correlation coefficient with 19 discriminant compounds. Using PCA, E. longifolia root samples were clearly discriminated from the products. This study showed that the developed online SPE-LC method was able to provide comprehensive evaluation of E. longifolia samples for quality control purposes.