IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI UNTUK MENINGKATKAN POLA PENJUALAN

Abstract

Medicine is a necessity for someone who is sold to people with disease. Therefore, every pharmacy or hospital must have a data processing system so that each transaction data can be used to make reports. From this report a useful result will be created to determine which drugs are most frequently purchased and sold so as to be able to determine the amount of stock at the pharmacy. But at the present time drug sales transaction data continues to increase every day so that it has accumulated because the system used is a system for storing or archiving bookkeeping without utilizing the transaction data, besides that the problem that often arises is the lack of maximum customer service at pharmacies because the drugs or needs that consumers are looking for are still not available. The a priori algorithm functions as a candidate for possible item combinations, then tests whether the combination meets the minimum support and minimum confidence parameters which are the threshold values ​​given by the user, so that it finds patterns in the form of products that will often be purchased together or products that tend to appear together in a transaction.