Providing Recommendations to New ILMCI Edu Voucher Customers Using the Market Basket Analyst Algorithm

Every company involved in the education business has sales data. One thing that really needs to be considered is the process of providing the best recommendations to customers. PT ILMCI INDONESIA as one of the companies involved in the education sector has not implemented the best recommendations regarding the education products offered, in running its business, of course, it is necessary to do good planning to increase the number of new customers. The purpose of this research is to provide the best recommendations to new customers in order to increase product sales by using sales data attributes from the sales process that has been done before. This recommendation analysis is carried out using market basket analysis algorithm, FP-Growth algorithm, W-Apriori algorithm, and W-Tertius. The highest confidence value from the market basket analysis algorithm is 67.6%. The highest support value generated from the FP-Growth algorithm is 70.2%. The highest confidence value from the W-Apriori algorithm is 63%. The highest confidence of the W-Tertius algorithm is 96.2%.