Production is a value-adding process that transforms raw materials into finished products to meet manufacturing requirements. Association rule analysis serves as a methodological approach to identify relationships between items, particularly in transactional datasets. This analytical method has proven effective in processing exchange data patterns. Analysis of production material usage patterns revealed that when items A and B are utilized, there exists a 50% probability of concurrent item C usage - a significant pattern emerging from transactional data analysis. The study generated association rules for each operational process. Empirical testing through RapidMiner Studio yielded consistent results, demonstrating linear relationships proportional to the modeled scenarios, thereby validating the model's applicability as a decision-making reference. The evaluation of generated association rules through RapidMiner Studio revealed a Lift Ratio value of 1. These results indicate that combinations meeting or exceeding a Lift Ratio threshold of 1 demonstrate statistical validity and practical utility.
Suwaryo et al. (Fri,) studied this question.