K-Means Clustering Implementation in Network Traffic Activities

Abstract

At present, management analysis bandwidth in a university is indispensable. It aims to control bandwidth usage, so that all spots can be served comfortably especially to supporting the teaching and learning activities. In this study, an analysis and clustering of the university internet traffic is required as bandwidth management decision support. Therefore, K-Means as a clustering algorithm bandwidth usage was implemented and explored. The results showed that the K-Means method can perform clustering with 3 and 4 clusters. The cluster is described high, medium and low bandwidth usage at certain times of each unit. Furthermore, the clustering result could be a recommendation management bandwidth for network administrator in order to planning, sharing, and controlling bandwidth.