K-Means Algorithm for Clustering Third-party Funds of Conventional Banking

Abstract

Banking business activities in Indonesia are very important for Indonesia's economic growth, one of which is by growing the investment sector through obtaining funds from the general public via third party funds. In this study, the third party funds discussed were third party funds from conventional banking. The purpose of this study is to group the Third party funds of Conventional Banking to obtain information on the development of Indonesia's economic growth, especially in conventional banking using the K-means. Research data in the form of conventional banking third party funds were obtained from the Financial Services Authority. The data are divided into 2 clusters: C1 (high) and C2 (low). Results show that 5 years have a low cluster (C1) and 6 years have a high cluster (C2). The findings of the analysis come in the form of information on the grouping of national banking third party funds to provide input to the Government of Indonesia, the Financial Services Authority, and Bank Indonesia in making policies on national banking.