Data Mining Pengelompokan Pengajuan Kredit Pensiun Pada Bank Sumut Menggunakan Metode Clustering (Studi Kasus : PT. Bank Sumut Cabang Binjai) - Alma Alawiyah Gultom; Budi Serasi Ginting; Magdalena Simanjuntak (Bulletin of Multi-Disciplinary Science and Applied Technology, 2022)
PT. Bank SUMUT Binjai branch is one of the financial institutions that provides several products offered to retirees such as retirement savings and pension loans. Most of the information is only seen as archives that are not used and can be destroyed at any time. This is a wrong view, because with proper and clever handling, these data can be processed and manipulated by data mining, so that later they can be used to produce useful information in making a decision. Data mining can help companies explore new knowledge by processing existing data with clustering methods and using the K-Means algorithm. From the credit application data, several criteria/variables will be taken, including the basic salary variables, allowances and loan guarantees (collateral) used. The data is processed with the Matlab program to produce a cluster center and the relationship between variables is obtained by the group with the highest value. The use of data mining techniques is expected to provide knowledge that was previously hidden in the data warehouse so that it becomes valuable information. The calculation that has been done is that the number of members of group 1 is 141 data, the number of members of group 2 is 90 data and the number of members of group 3 is 148 data. With the results centroid 1: 2.5319, 1, 1.5319, centroid 2: 5.2222, 3.5556, 1.9889 and centroid 3: 4,3286,1.8295, 2.1818.