Designing an Application for Analyzing Consumer Spending Patterns Using the Frequent Pattern Growth Algorithm

In this modern era, the market has been growing rapidly which can be seen from the navel shopping that is lined up in the hearts of big cities such as supermarkets, grocery stores and others that are provided to meet people's needs for primary goods that are always needed at all times. One of them is Giant Express Tamalanrea, a supermarket in the city of Makassar that serves the sale of household goods and general needs. With the use of customer data analysis to determine the customers' purchasing patterns, Giant Express can optimize the collation of goods, by positioning goods at closer shelves based on the level of frequency of goods purchased together by customers. Therefore, this study suggests the creation of an application to analyze consumer spending patterns using the frequent pattern growth algorithm method to ensure appropriate placement of goods to increase sales at Giant Express Tamalanrea. The purpose of this study is to develop an application that can analyze consumer spending patterns to increase sales by positioning goods based on consumer shopping patterns, as well as implementing the Frequent Pattern Growth Algorithm method to determine customer spending patterns to increase sales. Stages of research methods conducted begin with data collection at the study site, system requirements analysis, system design with UML, and system testing with the Black Box method.