Multi-criteria decision-making methods (MCDM) have an important role in various fields because they allow decision-makers to consider different aspects or criteria simultaneously. Weighted aggregate quantity product assessment (WASPAS) is a MCDM that combines the advantages of the weighted quantity model (WSM) and weighted product model (WPM) approaches. The challenge in ensuring the accuracy of the criteria weights using the WASPAS method lies in the sensitivity of this method to the given weight, which greatly affects the final result of the decision. Modifications are required in the WASPAS method to improve the accuracy and objectivity of weights, especially since weights have an important role in determining the final result. One approach that can be adopted is the integration of data-based methods using correlations between criteria. This modification not only improves the reliability of decision results, but also allows the WASPAS method to be more adaptive in dealing with complex and dynamic problems with interrelated criteria. The results of Pearson's correlation value from the combination of WASPAS with MEREC, ROC, and WASPAS-IC have a very strong correlation with each other. Meanwhile, Entropy had a lower correlation with other methods, but still showed a fairly good positive correlation with most methods, especially with WASPAS-IC which had a correlation of 0.947.