Abstract
The purpose of this study is to analyze the data mining of expired fertilizer returns from CV.YOLAND to the parent distributor using a dynamicsome algorithm which is expected to produce a more accurate output so that it will speed up the calculation process. The implementation of the dynamicsome algorithm uses methods from data mining which refer to Classification, Clustering, Association, Sequencing, Regression, Forecasting, Other Techniques and testing using the Tanagra software method. The analysis was carried out on an ongoing business process, then the results of the analysis were outlined in the Tanagra software which showed that it could accelerate the process of forming the trend of itemset combination patterns resulting from CV company data. Yoland, with the highest support and confidence is 0.25%. The application of the Dynamicsome Algorithm in data mining techniques is very efficient and can accelerate the process of forming the trend of itemset combination patterns.