<![CDATA[The current government policy is directed towards strengthening the MSME sector to achieve sustainable economic growth. The Ecoprint MSME in Lampung faces several challenges in maintaining the continuity of its business, including a decline in sales, limited capital and raw materials, as well as the unstable demand for ecoprint products, especially those that are still relatively new. This instability makes it difficult for MSMEs to manage inventory, which hinders the production process. The research method to address the issue of applying Business Intelligence in the strategy for developing superior products in ecoprint MSMEs using the Apriori Algorithm can be approached through Business Intelligence methods. The data used in this study is sales transaction data from June to August 2024. The stages of applying Business Intelligence include Justification, Planning, Business Analysis, Design, and Construction. By applying Business Intelligence and the Apriori Algorithm, MSMEs can compete in the digital era and achieve sustainable success. Based on testing results using Rapidminer, three association rules were obtained: Dress, Hijab with a support of 57% and confidence of 100%; Hijab, Dress with a support of 57% and confidence of 80%; and Hijab, Accessories with a support of 57% and confidence of 80%. The Apriori algorithm is capable of identifying consumer purchase patterns, allowing MSMEs to determine the most in-demand products and adjust their production strategy accordingly. The application of the Apriori algorithm on transaction data has resulted in various unique association rules. The key difference between these rules lies in the combinations of related products. Further analysis shows that the performance of the Apriori algorithm is optimal when using a minimum support value of 50% and a minimum confidence of 80%.]]>
