ANALISIS PENJUALAN PADA ALTAH INDAH MART MENGGUNAKAN FREQUENT PATTERN GROWTH ALGORITHM

Abstract

The development of technology and consumer purchasing lifestyles has reduced the existence of traditional markets, because people are more interested in shopping at modern markets such as hypermarkets, supermarkets, and minimarkets. Altah Indah Mart is one of the minimarkets located in Kupang city. Generally, every modern market uses a computerized system to store sales and purchase data that produces transaction data. The resulting transaction data can be used as an important source of information to predict and plan product sales according to consumer buying patterns. The technological approach can be done using data mining techniques, namely Association Rules Mining which focuses on finding consumer purchasing patterns by analyzing shopping baskets. Data collection was carried out through field studies, namely by observing and asking for data directly at Altah Indah Mart. Existing sales transaction data will be processed using the Frequent Pattern Growth Algorithm. The results obtained from processing the sales transaction data are in the form of a combination of items (itemset) with association values, namely the value of support and confidence. At the testing stage, high-frequency pattern analysis was used and determined associative patterns to see consumer buying patterns based on sales data.