Abstract :
In marketing a product, there are several factors that affect a sale. If you have
a good sales strategy, then a product will sell quickly, but if the strategy used is not
right, then the product will decline in terms of sales. With buying and selling
activities to consumers every day it is getting higher and higher, so this can create
a bigger pile of data. To provide goods in accordance with consumer demand in a
store, it is necessary to conduct research and planning that can predict consumer
demand. This study uses the a priori algorithm method, so that it can determine the
percentage of sales and the close relationship between goods so as to reduce
spending on goods that are less attractive to consumers. This research has succeeded
in implementing the a priori algorithm in an application that is used to process sales
transaction data, resulting in a consumer buying pattern that tends to occur from a
combination of available items