Abstract:
At this time, the retail sector in Indonesia continues to experience significant growth, with
an increase in the number of outlets built in various locations. In sales places such as
shops, sales transactions are carried out every day, and the number is increasing. The LS
Mart shop is a sales place that provides household necessities, food, and people's daily
necessities, which are generally sold. An effective and efficient sales strategy is needed
to attract customer interest and comfort when shopping, but the sales transaction data
that we have has not been used to dig up this information. It is very important to have
knowledge of the required strategy. Existing sales transaction data is used to find
purchasing patterns and determine sales strategy recommendations using the association
rule method using the ECLAT algorithm. ECLAT is an association algorithm that
identifies the most frequently repeated itemsets and is one of the association algorithms
with the most effective search for frequently repeated itemsets when compared to other
algorithms. The results of data processing showed that the ECLAT algorithm was
successfully applied to determine product purchasing patterns. Sales transaction data
processing resulted in 12 rules for 2-itemset combinations and also nine rules for 3-
itemset combinations, as well as recommendations for sales strategies that can be
implemented in the form of bidding strategies, packages, and product placement
strategies.
