Penerapan Algoritma Apriori dalam Menganalisis Pola Minat Beli Konsumen di Coffee Shop - Renaldi Nur Fahrizal; Ita Arfyanti; Ulfah Nurfadhila (Bulletin of Computer Science Research, 2026)
The currently intensive increase in competition within the cafe industry demands that business operators, such as Coffee shop Zecoff Tenggarong, not only focus on product quality but also gain a deep understanding of consumer behavior and buying interest patterns. This understanding is crucial for formulating targeted and sustainable business strategies. This research specifically focuses on analyzing consumer buying interest patterns at Coffee shop Zecoff Tenggarong through the identification of products that tend to be purchased together in a single transaction. To achieve this objective, the study employs a Data Mining approach using the Association Rule Mining technique. The core method implemented on the cafe's sales transaction data over a specific period is the Apriori Algorithm. This algorithm was chosen due to its effectiveness in processing large datasets and identifying frequently co-occurring itemsets. The data analysis process includes the stage of determining critical parameters: support (the frequency degree of the itemset), confidence (the strength of the causal relationship), and lift (the value of association improvement), which are collectively used to filter and generate the strongest and most relevant association rules. The empirical results of the study show that the Apriori Algorithm is highly effective in uncovering hidden purchasing patterns that are difficult to detect through conventional data analysis. The strong association rules derived from this mining process provide important and actionable information for the owner of Zecoff Tenggarong. The strategic implications of these findings include: formulating more targeted cross-selling marketing strategies (for example, recommending companion products that are certainly in demand), optimizing product arrangement (placing strongly associated items in close proximity), and increasing inventory management efficiency (ensuring that items frequently bought together are always in stock). In conclusion, this research concludes that the utilization of Data Mining technology with the Apriori Algorithm is a vital and transformative tool. It not only supports daily operational decision-making but also significantly enhances the coffee shop's competitiveness amidst a tight market rivalry.