Association Rule Mining using FP-Growth Algorithm to Prevent Maverick Buying

Maverick Buying describes unwelcome behaviour in the field of corporate purchasing management. It is a purchasing made outside the purchasing and procurement processes. Neddy Enterprise Sdn. Bhd (NE) is an electrical company that often takes a project from a government agency. NE needs to buy supplies to use them in a specific project. However, the purchasing and operational strategy are not fully optimised, where the maverick buying process has been identified in the initial phase of the study. When NE received a project from their customer in the regular operation, the project supervisor will decide the supplies needed. However, that did not happen in NE. From January to December 2019, some supplies have been purchased for every month in a small quantity. This paper aims to help NE in making decisions, especially in planning for their supply purchasing. Association rule mining has been used to associate the relationship between the supply needed and the projects acquired. Cross-Industry Standard Process for Data Mining (CRISP-DM) has been used as a project framework to carry out this research. As a result, several supplies are associated with a specific type of project. This finding will help NE to make better purchasing planning.