Clustering Bandwidth Usage in Higher Education using K-Means, Agglomerate, KMedoids Algorithm
Danial
Direktorat Sistem dan Teknologi Informasi, Institut Teknologi Bandung
Jalan Ganesa 10, Bandung 40132, Indonesia
Abstract
In Indonesia, bandwidth usage management in higher education is still a great challenge. Every year, the internet bandwidth and the budget are higher, but the growth of scientific publication to the cumulative universities is still under the other countries in ASEAN. In the other side, the universities have not measure the effective of usage bandwidth for their activities. The log data is managed rarely. The user and data can be clustered. So the management have the picture for their bandwidth policies. In this paper, there will be comparing the clustering that using Agglomerate, K-Means, and K-Means algorithms. The results is to find the best clustering and make a pattern for ITB network usage. The method is implemented in real data in ITB network. The campus management will have a good data and information for their policies of bandwidth management.
Keywords: Clustering, Bandwidth Management, Data Management, Internet
Topic: Artificial Intelligent and soft computing