PREDIKSI KEMACETAN PADA JARINGAN KOMPUTER MENGGUNAKAN METODE NAIVE BAYESIAN CLASSIFIER
DOI:
https://doi.org/10.33005/santika.v2i0.92Keywords:
jaringan, komputer, bayesian, kemacetan, manajemen, prediksi.Abstract
Berdasarkan pada studi terkini mengenai kecepatan internet, Jepang menduduki posisi kedua setelah Korea sebagai negara yang memiliki akses internet tercepat di dunia. Dibandingkan dengan Indonesia, yang menduduki posisi 63, hal ini menunjukkan rendahnya kualitas pelayanan jaringan komputer, khususnya dalam aplikasi internet di Indonesia.Melihal hal ini maka perlu dikaji dan diteliti bagaimana cara pemecahan permasalahannya. Pada makalah ini, diajukan salah satu metode untuk meningkatkan kualitas jaringan komputer dengan menghindari beberapa masalah menggunakan prediksi permasalahan yang akan terjadi pada jaringan komputer dengan menggunakan Naïve Bayesian Classifier.
References
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[2] Bottone, S.; Lee, D.; O'Sullivan, M.; Spivack, M.;, “Failure prediction and diagnosis for satellite monitoring systems using Bayesian networks”, MILCOM 2008. IEEE, 16-19 Nov. 2008 Page(s):1– 7.
[3] Clemm Alexander, “Network Management Fundamentals”, Cisco Press, 2006.
[4] Chandramouli, Y., Neidhardt, Arnold., “Analysis of Network Congestion Inference Techniques”, Sigmetrics Performance Evaluation Review, Vol. 3 Issue 4, 2005.
[5] Whelzl, Michael., “Network Congestion Control”., John Wiley & Sons Ltd., 2005.
[6] Heckerman, D., “A Tutorial on Learning With Bayesian Networks, in Learning in Graphical Models”, M. I. Jordan, editor, MIT Press, 1998.
[7] Steinder. M, Sethi, A.S. “End to end services Failure Diagnosis Using Belief Networks”, NOM IEEE/IFIP, 2002.
[8] Hood, C.S.; Ji C.; “Probabilistic Network Fault Detection”, Global Telecommunication Conference, 1996, GLOBECOM’96, Vol. 3, 18-22 Nov. 1996. Page(s):1872-1876.
[9] O. Wolfson, S. Sengupta, Y. Yemini, “Managing Communication Networks by Monitoring Databases”, IEEE transactions on software Engineering, Vol. 17, no. 9, 1991.
[10] Y.Motomura, I.Hara, "Bayesian Network Learning System based on Neural Networks", AFSS2000, International Symposium on Theory and Applications of Soft Computing (2000).
[11] NS2. http://www.isi.edu/nsnam/ns/. Last Access, July 26, 2010.
[12] Wallin, S.: Chasing a Definition of “Alarm”. J Netw Syst Manage (2009) 17:457-481. doi: 10.1007/s10922-009-9127-3
[13] B-Course. “A Web-based data analysis tool for Bayesian modeling”. Complex Systems Computation Group (CosCo) Helsinki Institute for Information Technology. http://b- course.cs.helsinki.fi/obc/. Last access, July 26, 2010.
[14] Essam S. Ali and M.G. Darwish. “Diagnosing Network Fault using Bayesian and Case-based Reasoning Techniques”. In Proceedings of ICCES 2007. Page(s): 145-150. doi: 10.1109/ICCES.2007.4447040
[15] BAYONET, “Bayesian Network Construction System”. National Institute of Advanced Industrial Science and Technology. http://www.msi.co.jp/BAYONET/. Last access, July 14, 2010.
[16] Erwin Harahap, Wataru Sakamoto, Hiroaki Nishi. “Failure Prediction Method for Network Management System by using Bayesian Network and Shared Database”. In Proceeding of the APSITT 2010. IEEE Asia-Pasific Symposium on Information and Telecommunication Technologies.
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Published
2021-11-25
How to Cite
Maulana, H., & Mufreni, S. L. (2021). PREDIKSI KEMACETAN PADA JARINGAN KOMPUTER MENGGUNAKAN METODE NAIVE BAYESIAN CLASSIFIER. Prosiding Seminar Nasional Informatika Bela Negara, 2, 41–43. https://doi.org/10.33005/santika.v2i0.92
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