Merchant segmentation using K-modes clustering as QRIS marketing recommendations.

Customer segmentation plays a vital role in the formulation of marketing strategies. This work needs to be done by companies to design different strategies to maximize user value. QRIS is the latest product from Bank Indonesia that needs to be introduced to users. User profiles that are categorical data are used to segment customers of QRIS. Therefore, this work implemented the K-Modes Clustering algorithm to segment customers on the QRIS merchant dataset to determine the proper marketing strategy. The scenario of experiments was performed to obtain segmented customers. Considering the Dunn index, several features of segmented customers are from most clusters. These features have been analyzed and are accepted and proven as the segmented customer recommended by the authority of QRIS. The commonly obtained features of merchants are a micro business, business wholesaler, located in Makassar, male and aged. [ABSTRACT FROM AUTHOR]