COMPARISON OF APRIORI AND FP-GROWTH ALGORITHMS ON DETERMINATION OF ASSOCIATION RULES IN AUTHORIZED AUTOMOBILE SERVICE CENTRES

Data Mining is used to describe the totality of techniques which aim to find the unexplored patterns in a set of data. The purpose of data mining is to create models of decision-making devoted to estimations of future behavior based on analysis of past activities. In this study the shopping data of the customers of an authorized service, operating in the automative sector in Turkey, were analyzed using Apriori and FP-Growth Algorithms. This way, it is observed which products were purchased together by customers and in line with this observation, campaigns and promotions were given a direction to increase the profit.