Improvement of Performance E-Learning Moodle Service in Vocational High School with Optimization of Web Server and Database Server

Rahmatul Irfan, Universitas Negeri Yogyakarta, Indonesia
Cannavaro Yogi Pratama, Universitas Negeri Yogyakarta, Indonesia

Abstract


Since COVID-19, online learning has taken on an increasingly prominent role. Moodle is a popular online learning platform. Its implementation necessitates various support components, including a web server and an e-learning database server. The purpose of this study is to examine the optimization of web servers and database servers when there are multiple large connections at SMK N 2 Depok's E-learning. A pre-experimental one-group pretest-posttest design was used to conduct experimental research before and after optimization. Response time and throughput performance variables are used to assess performance on the Web Server, whereas response time and transaction per second performance are measured on the Database Server. The tools utilized in this study were Apache Benchmark and Sysbench. The population in this study was 2180 active users, with a total sample of 338 connections to access e-learning. The results of this research indicate that the performance of the Moodle e-learning web server can be optimized by tuning the web server configuration. There was a significant increase in performance on the web server after optimization. The performance of the moodle e-learning database server performance can be optimized by optimizing the database server configuration tuning.  There is a significant increase in the performance of the database server after optimization. To use e-learning efficiently when using several connections at the same time, the web server and database server must be optimized through server tuning. This can boost the effectiveness of e-learning in the classroom. As a result, e-learning developers should consider optimizing e-learning server settings.


Keywords


System optimization; web server; database server; moodle; e-learning

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DOI: https://doi.org/10.21831/elinvo.v9i1.42878

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