<![CDATA[Toko Shaliha Parfume menyediakan produk parfume dengan berbagai macam merk dan varian. Kegiatan penjualan dilakukan setiap hari maka dari itu data transaksi penjualan akan meningkat dan menumpuk. Data penjualan pada toko shaliha parfume hanya dipakai sebagai rekap penjualan dan arsip. Peneliti tertarik untuk menerapkan algoritma association rule yaitu algoritma apriori untuk memberikan informasi minimum support yang paling sesuai dengan kebutuhan untuk menghasilkan frequent itemset tertinggi. Hasil yang didapat yaitu, N dengan support 66,67%, AB dengan support 66,67%, dan hasil yang memenuhi syarat minimum confidence 80% seperti jika membeli N maka akan membeli AB dengan confidence yang diperoleh 80%, jika membeli AB maka akan membeli N dengan confidence yang diperoleh confidence 100%. Abstract: Shaliha Parfume shop provides perfume products with various brands and variants. Sales activities are carried out every day and of course sales transaction data will increase and accumulate. Sales data at the shaliha parfume store is currently only used as a sales recap and archive. Wrong or the current problem is that Salihha Parfume has difficulty doing good stock management for smooth sales transactions at the store. Therefore, the researcher uses the association rule which is the result of the a priori algorithm that produces the minimum supporting information value or support that best suits the needs and the most appropriate certainty or confident value. Based on the final association rules, it is known that the results obtained are, N with 66.67% support, AB with 66.67% support. with this pattern the management can manage the stock of goods that are most desirable and less desirable by customers and can develop sales strategies to be able to increase sales of perfume products in the store.]]>
