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Jami’in, Mohammad Abu
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Computer Science & IT

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Performance Evaluation of Web Applications Using JMeter Load Testing for Server Capacity and Response Efficiency Annisa, Aulia; Ardiana, Mirza; Rahayu, Putri Nur; Brian, Thomas; Jami’in, Mohammad Abu
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11840

Abstract

The reliability of web-based conference systems is crucial for ensuring smooth services during periods of high activity. This research evaluates the performance of the ICOMTA PPNS journal website by conducting load testing using Apache JMeter with scenarios ranging from 50 to 5000 virtual users, each executed for one hour. The evaluation focuses on response time, error rate, throughput, and bandwidth usage. The results indicate that the website performs reliably with up to 200 concurrent users, demonstrating stable response times and no recorded errors. However, once the load surpasses 300 users, response times increase sharply exceeding 60 seconds and errors begin to appear, suggesting that the server has reached its performance limit. Under the heaviest load of 5000 users, throughput continues to rise, but overall service quality declines significantly. These findings highlight the need for server enhancements or migration to cloud-based infrastructure to ensure stable performance during peak usage.
Minimum-Variance Pitch Control of a Small-Scale Wind Turbine Using a Switching Quasi-ARX Neural Network Under Low and Intermittent Winds Ciptaningrum, Adiratna; Echsony, Mohammad Erik; Leonard, Rikky; Jami’in, Mohammad Abu
Journal of Applied Informatics and Computing Vol. 10 No. 5 (2026): October 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i5.14029

Abstract

Adaptive pitch control built on the quasi-ARX neural network (QARXNN) has so far been reported for wind energy conversion systems (WECS) purely in simulation, driven by artificially generated wind sequences and parameterised for utility-scale machines. The present work carries the scheme over to a small rotor of 1 m radius, typical of distributed installations in low-wind classes, and tests it against two field records of wind speed, temperature and pressure acquired with a low-cost Arduino-based weather station at Gili Raja and Mandangin Island, Madura, East Java, Indonesia. Three departures from the published formulation are documented: a sign convention in the drivetrain torque balance is corrected, the model order is lowered to match the limited length of the field records, and the minimum-variance pitch law is re-derived for the reduced-order structure. Two alternative nonlinear cores for the quasi-ARX regression, a radial-basis-function network and an Elman recurrent network, are also set out and weighed against the multilayer-perceptron core adopted here. In closed-loop simulation driven by the measured wind, the QARXNN minimum-variance controller lowers rotor-speed tracking RMSE by 9.1% and 5.2% against a carefully tuned fixed-gain PI baseline on the two records, with the nonlinear branch of the model active for roughly a quarter of the samples. Feeding the raw, coarsely quantised anemometer signal into the loop shrinks this margin considerably, an outcome traced to the mechanical bandwidth of the rotor rather than to either control law. The study is therefore offered as a proof-of-concept field validation and not as a long-term resource assessment.
Co-Authors Adiratna Ciptaningrum Annisa, Aulia Ardiana, Mirza Brian, Thomas Leonard, Rikky Rahayu, Putri Nur