Proceedings of the 2022 Annual Technology, Applied Science and Engineering Conference (ATASEC 2022)

<Previous Article In Volume
Next Article In Volume>

Performance Analysis of Mobile Learning Systems on Cloud Computing Using Load Testing Methods

Authors
Yuri Ariyanto1, *, Budi Harijanto1, Atiqah Nurul Asri1, A. Yahya Hudan Permana1, Muhammad Nuruddin Ismail1, Sofyan Noor Arief1
1State Polytechnic of Malang, Malang, 65142, Indonesia
*Corresponding author. Email: yuri@polinema.ac.id
Corresponding Author
Yuri Ariyanto
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-106-7_12How to use a DOI?
Keywords
Apache JMeter; Cloud Server; Load Testing; Mobile Learning
Abstract

Along with developing the Mobile Learning System, Mobile Learning requires adequate facilities, such as a server as a storage medium and as a provider of an API-based web service, especially when there are more and more Mobile Learning users. And to ensure the quality of the web service, a system test is needed, namely Load Testing. The load testing method uses Apache JMeter tools to check and test the performance of a server. Load testing is done by testing the existing web services on the cloud server where there are 4 web servers, 1 database server, and 1 load balancing server. Scenario testing is based on load data of 100, 500, and 1000 within 10 seconds. The results obtained from the test data are the average test time with a consistent value in each scenario, with the throughput value getting a very good value because the higher the request is given. The HAProxy server is running well in sharing requests to each server with an error value of 0%.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 Annual Technology, Applied Science and Engineering Conference (ATASEC 2022)
Series
Advances in Engineering Research
Publication Date
29 December 2022
ISBN
978-94-6463-106-7
ISSN
2352-5401
DOI
10.2991/978-94-6463-106-7_12How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yuri Ariyanto
AU  - Budi Harijanto
AU  - Atiqah Nurul Asri
AU  - A. Yahya Hudan Permana
AU  - Muhammad Nuruddin Ismail
AU  - Sofyan Noor Arief
PY  - 2022
DA  - 2022/12/29
TI  - Performance Analysis of Mobile Learning Systems on Cloud Computing Using Load Testing Methods
BT  - Proceedings of the 2022 Annual Technology, Applied Science and Engineering Conference (ATASEC 2022)
PB  - Atlantis Press
SP  - 125
EP  - 133
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-106-7_12
DO  - 10.2991/978-94-6463-106-7_12
ID  - Ariyanto2022
ER  -