Server Network Monitoring Notifications and Cluster Analysis through Web Application

Authors

  • Eidelbert Suherianto Sinaga Master Program in Computational Science, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha No. 10, Bandung, 40132, Indonesia
  • M Zaky Erdiansyah Master Program in Computational Science, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha No. 10, Bandung, 40132, Indonesia
  • Aziz Mustika Aji Master Program in Computational Science, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha No. 10, Bandung, 40132, Indonesia
  • Atthar Luqman Ivansyah Master Program in Computational Science, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha No. 10, Bandung, 40132, Indonesia

Keywords:

server network monitoring, notification, cluster, zabbix, web application, telegram

Abstract

A web-based local server monitoring application using Zabbix monitoring tools was developed to fulfill the requirement of monitoring the status of network downtime and network uptime. One of the main requirements is the ability to get real-time notifications if the server has a network problem so that mitigation actions can be taken quickly. In addition, this application is also completed with the feature of sending server downtime and uptime network status to mobile applications (Telegram) and website applications built using the PHP programming language and MySQL database. By sending the status of server network problems to the website that was built, it is useful to illustrate trends and analyze patterns of server network problems, as well as analyze cluster servers based on total network disruption. With this recapitulation, network administrators can make better evaluations and planning to improve server reliability and reduce potential downtime in the future. The Zabbix monitoring tool was chosen because of its comprehensive and flexible ability to monitor various server parameters and the ease of managing and displaying data through an intuitive web interface. The results of this implementation are expected to improve operational efficiency and maintain the continuity of services offered by the server.

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References

J. Renita, B. Noble, and N. Edna Elizabeth, “Network’s Server Monitoring and Analysis Using Nagios,” 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), doi: 10.1109/WiSPNET.2017.8300092

A. Mardiyono, W. Sholihah and F. Hakim, “Mobile-based Network Monitoring System Using Zabbix and Telegram,” 2020 3rd International Conference on Computer and Informatics Engineering (IC2IE), doi: 10.1109/IC2IE50715.2020.9274582

S. S. Kamenov, “Experimental monitoring on network based tactile sensing system,” 2019 28th Int. Sci. Conf. Electron. 2019 - Proc., pp. 1–4, 2019, doi: 10.1109/ET.2019.8878661.

A. Hidra, Defni., D. Prayama, and F. Agustin, “Design and Implementation of Network Monitoring System Using Nagios with Email and SMS Alert,” J. Ilm. Poli Rekayasa, vol. 10, no. 1, p. 42, 2014, doi: 10.30630/jipr.10.1.56.

Y. G. Shan, L. Chao, G. Guangjian and F. Gao, "Research on Monitoring of Information Equipment Based on Zabbix for Power Supply Company," 2021 3rd International Conference on Applied Machine Learning (ICAML), Changsha, China, 2021, pp. 487-491, doi: 10.1109/ICAML54311.2021.00108.

J. Kiruthika, S. Khaddaj, D. Greenhill and J. Francik, "User Experience Design in Web Applications," 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES), Paris, France, 2016, pp. 642-646, doi: 10.1109/CSE-EUC-DCABES.2016.253.

Telegram, "Telegram APIs," Telegram, [Online]. Available: https://core.telegram.org/. [Accessed 12 08 2020].

T. Sutikno, L. Handayani, D. Stiawan, M. A. Riyadi and I. M. I. Subroto, "Whatsapp, Viber and Telegram: which is the Best for Instant Messanging?," International Journal of Electrical and Computer Engineering (IJECE), vol. 6, no. 3, pp. 909-914, 2016.

A. K. Jain, “Data clustering: 50 years beyond K-means,” Pattern Recognit. Lett., vol. 31, no. 8, pp. 651–666, 2010.

R. Xu and D. Wunsch, “Survey of clustering algorithms,” IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 645–678, May 2005.

J. Macqueen, “Some methods for classification and analysis of multivariate observations,” in

S. P. Lloyd, “Least squares quantization in PCM,” IEEE Trans. Inf. Theory, vol. 28, pp. 129–136, Mar. 1982.

S. Soundararajan, J. D. Arthur, and O. Balci, “A methodology for assessing agile software developemtn methods,” Agile Conference, Aug 2012, doi: 10.1109/Agile.2012.24.

P. Mary and T. Poppendieck, “Lean software development: An agile toolkit,” Nachdr., Addison-Wesley, 2010.

R. Polk, “Agile and kanban in coordination,” in Proc. Agile Conf., 2011, pp. 263–268.

Paula Zenni Lodetti, Edison A. C. Aranha Neto et al., “MAE and RMSE Analysis of K-means Predictive Algorithm for Photovoltaic Generation”, International Conference on Electrical, Computer and Energy Technologies (ICECET), Prague, Czech, 20-22 July 2022.

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Published

2025-01-20

How to Cite

Sinaga, E. S., M Zaky Erdiansyah, Aji, A. M., & Ivansyah, A. L. (2025). Server Network Monitoring Notifications and Cluster Analysis through Web Application. ITB Graduate School Conference, 4(1). Retrieved from https://gcs.itb.ac.id/proceeding-igsc/index.php/igsc/article/view/297

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Articles