Assessing University Website Performance: A Comparative Analysis Using GTmetrix

Authors

  • Davin Nayaka Pandya Bina Nusantara University
  • Doddy Suryadharma Bina Nusantara University
  • Lili Ayu Wulandhari Bina Nusantara University
  • Islam Nur Alam Bina Nusantara University

DOI:

https://doi.org/10.21512/ijcshai.v1i1.12152

Keywords:

Website Performance, Comparative Analysis, GTmetrix Evaluation

Abstract

As the reliance on websites to disseminate information increases, universities are no exception, using websites as an important platform for their information systems. However, ensuring optimal website performance is imperative, as slow or unresponsive websites can lead to decreased user satisfaction and affect the university's reputation. This study aims to analyze and compare the performance of university information system websites from Indonesia’s top five universities against the world’s leading institutions in Computer Science and Information Systems based on QS World University Rankings by Subject 2023. Utilizing GTmetrix, a comprehensive performance assessment tool, key performance metrics such as First Contentful Paint (FCP), Speed Index (SI), Largest Contentful Paint (LCP), Time to Interactive (TTI), Total Blocking Time (TBT), and Cumulative Layout Shift (CLS) were evaluated. The findings reveal a significant performance gap between the top universities globally and in Indonesia. While global universities demonstrate good performance across various metrics, Indonesian universities exhibit areas in need of improvement, particularly in metrics like FCP, SI, LCP, TTI, and CLS. Nevertheless, Indonesian universities excel in blocking time, suggesting strategic strengths that can be leveraged for overall performance enhancement. This study underscores the importance of regular attention to website performance to enhance user experience and maintain the university's reputation within the academic community.

Dimensions

Author Biographies

Davin Nayaka Pandya, Bina Nusantara University

Computer Science Department, School of Computer Science

Doddy Suryadharma, Bina Nusantara University

Computer Science Department, School of Computer Science

Lili Ayu Wulandhari, Bina Nusantara University

Computer Science Department, School of Computer Science

Islam Nur Alam, Bina Nusantara University

Computer Science Department, School of Computer Science

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Published

2024-10-10

How to Cite

Pandya, D. N., Suryadharma, D., Wulandhari, L. A., & Alam, I. N. (2024). Assessing University Website Performance: A Comparative Analysis Using GTmetrix. International Journal of Computer Science and Humanitarian AI, 1(1), 33–38. https://doi.org/10.21512/ijcshai.v1i1.12152

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