Penerapan Data Mining Menggunakan Algoritma K-Medoids Dalam Pengelompokan Nasabah Penerima Reward Pada PT Dotri Gadai Jaya - Meniati Zebua; Rizki Muliono (Mahesa Research Institute, 2024)
The increasing growth of the financial industry makes companies experience intense competitive pressure. PT Dotri Gadai Jaya (PT DGJ) is a private pawnshop company, facing challenges in maintaining and increasing customer loyalty amidst this competition. One of the strategies used by PT DGJ is to provide rewards to customers based on the number of pawn loan transactions. However, companies experience difficulties in grouping reward recipient customers efficiently and accurately. To overcome this problem, it is necessary to apply data mining using the K-Medoids algorithm. The main objective of this research is to apply the K-Medoids algorithm in grouping reward recipient customers at PT DGJ, knowing the grouping results, and evaluating the results using the Davies Bouldin Index (DBI). The results of the grouping of 1,085 customers are 314 customers who received a 30% reward, 540 customers with a 20% reward and 231 customers with a 10% reward. The cluster evaluation result using DBI is 0.368812, which means the cluster quality value is close to 0 or is quite small. So it can be said that the resulting cluster is quite good.