Pengembangan Graph Mining untuk Prediksi Jaringan Kerja Sistem Pembayaran dalam Real Time Gross Settlement Berbasis Clearing House

Abstract

This research develops the settlement mechanism in the Real Time Gross Settlement using so called clearing house through a serious game method. In this approach banks are represented as nodes that do the settlement process according to the simple rules. Moreover, the graph mining approach is used for predicting the activity networks on those banks. As the result, for constant nodes indicate that the more the activity networks among banks are available, the more the activity networks can be identified. Furthermore, the smaller the differences among the bank health’s level are, the greater the network activities can be identified. This behavior is a consequence of chosen fixed point assumption.