Web Information System for E-Sport Arena Community with OWASP-Based Cybersecurity Using XP Method

  • Afgha Aufan Amikom University Purwokerto, Indonesia
  • Purwadi Purwadi Amikom University Purwokerto, Indonesia
  • Argiyan Dwi Pritama Amikom University Purwokerto, Indonesia
Keywords: e-sports community, web information system, Extreme Programming, OWASP Top 10, cybersecurity, usability

Abstract

The rapid development of the e-sports ecosystem in Purwokerto has encouraged the emergence of digital communities such as the Esport Arena Community. However, the management of member data, event information, and merchandise transactions is still carried out manually through social media, resulting in inefficiency and limited-service reliability. This study aims to develop a web-based information system that integrates member management, jersey evolution documentation, and secure online merchandise transactions. The system was developed using the Extreme Programming (XP) method, which supports iterative development and continuous refinement. Security measures were implemented based on OWASP Top 10 recommendations, including prepared statements, input validation, CSRF protection, and Role-Based Access Control (RBAC). System evaluation using the System Usability Scale (SUS) produced a score of 88, categorized as Excellent, indicating high user satisfaction and strong usability performance. The results demonstrate that the system operates securely, reliably, and effectively improves operational efficiency for the Esport Arena Community.

Downloads

Download data is not yet available.

References

P. D. K. Sujata, S. B. Sardjono, and S. P. Hendratno, “Esport ecosystem, financial behavior, and carbon emissions in Indonesian urban area,” in Proc. 4th Asia Pacific Information Technology Conf., New York, USA, 2022, pp. 123–130, doi: 10.1145/3512353.3512371.

S. A. Pradana, R. M. Pikahulan, M. A. Alvian, and S. Adriana, “Regulation of esports in the context of employment in Indonesia,” Amsir Law Journal, vol. 4, no. 1, pp. 15–31, Oct. 2022, doi: 10.36746/alj.v4i1.98.

S. D. Hilda, N. Heryana, and A. A. Ridha, “Website security analysis for Curug Village Government using the Open Web Application Security Project (OWASP),” Jurnal Informatika dan Teknik Elektro Terapan, vol. 12, no. 3S1, Oct. 2024, doi: 10.23960/jitet.v12i3S1.5236.

M. Syarifudin, L. Widyawati, and O. Asroni, “Web security vulnerability analysis and mitigation based on OWASP Top 10,” Journal of Artificial Intelligence and Engineering Applications, vol. 4, no. 3, pp. 1829–1834, Jun. 2025, doi: 10.59934/jaiea.v4i3.1029.

I. Purnama, “Clinical information system using Extreme Programming method,” International Journal of Science, Technology & Management, vol. 4, no. 5, pp. 1229–1235, Sep. 2023, doi: 10.46729/ijstm.v4i5.931.

O. Fenardi and F. S. Lee, “Aplikasi akademik berbasis website menggunakan metode Extreme Programming pada SMAN 1 Belinyu,” Jurnal Teknologi dan Sistem Informasi Bisnis, vol. 5, no. 4, pp. 440–447, Oct. 2023, doi: 10.47233/jteksis.v5i4.843.

S. D. Pohan and I. Firdaus, “Implementation of Extreme Programming method in the development of Pekanbaru community training information system,” Cyberspace: Jurnal Pendidikan Teknologi Informasi, vol. 6, no. 1, pp. 20–29, Mar. 2022, doi: 10.22373/cj.v6i1.11851.

D. Priyawati, S. Rokhmah, and I. C. Utomo, “Website vulnerability testing and analysis of website applications using OWASP,” International Journal of Computer and Information System, vol. 3, no. 3, pp. 142–147, Aug. 2022, doi: 10.29040/ijcis.v3i3.90.

O. Iparraguirre-Villanueva, F. Sierra-Linan, and M. Cabanillas-Carbonell, “Location-based mobile application for blood donor search,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 4, pp. 1–7, 2022, doi: 10.14569/IJACSA.2022.0130418.

F. P. E. Putra et al., “Systematic literature review: Security gap detection on websites using OWASP ZAP,” Brilliance: Research of Artificial Intelligence, vol. 4, no. 1, pp. 348–355, Jul. 2024, doi: 10.47709/brilliance.v4i1.4227.

O. Suria, “A statistical analysis of System Usability Scale (SUS) evaluations in online learning platforms,” Journal of Information Systems and Informatics, vol. 6, no. 2, pp. 992–1007, Jun. 2024, doi: 10.51519/journalisi.v6i2.750.

P. Palee, P. Wannapiroon, and P. Nilsook, “The architecture of intelligent career prediction system based on cognitive technology,” International Journal of Advanced Computer Science and Applications, vol. 11, no. 12, pp. 1–8, 2020, doi: 10.14569/IJACSA.2020.0111214.

M. L. Sheng, N. Natalia, and C. Y. Hsieh, “Reconceptualizing value creation: Exploring the role of goal congruence in the co-creation process,” Journal of Retailing and Consumer Services, vol. 66, p. 102947, May 2022, doi: 10.1016/j.jretconser.2022.102947.

T. Carsault, J. Nika, P. Esling, and G. Assayag, “Combining real-time extraction and prediction of musical chord progressions,” Electronics, vol. 10, no. 21, p. 2634, Oct. 2021, doi: 10.3390/electronics10212634.

M. A. Hassan, Z. Shukur, and M. K. Hasan, “An efficient secure electronic payment system for e-commerce,” Computers, vol. 9, no. 3, p. 66, Aug. 2020, doi: 10.3390/computers9030066.

A. Karalko et al., “In vivo contrast imaging of rat heart with carbon dioxide foam,” Sensors, vol. 22, no. 14, p. 5124, Jul. 2022, doi: 10.3390/s22145124.

Y. Luo, S. Duan, and X. Xu, “FPGA-PRO: A defense framework against crosstalk-induced secret leakage in FPGA,” ACM Transactions on Design Automation of Electronic Systems, vol. 27, no. 3, pp. 1–31, May 2022, doi: 10.1145/3491214.

Y. Wang et al., “Computer prediction of seawater sensor parameters in the Central Arctic region based on hybrid machine-learning algorithms,” IEEE Access, vol. 8, pp. 213783–213798, 2020, doi: 10.1109/ACCESS.2020.3038570.

K. Chattrairat, W. Wongseree, and A. Leelasantitham, “Comparisons of machine-learning methods for statistical downscaling,” Journal of Web Engineering, vol. 20, no. 5, pp. 1–12, Jul. 2021, doi: 10.13052/jwe1540-9589.2057.

Z. Zhang and L. Dai, “Effects of synaptic pruning on phase synchronization in chimera states of neural networks,” Applied Sciences, vol. 12, no. 4, p. 1942, Feb. 2022, doi: 10.3390/app12041942.

A. Pradhan et al., “Biosensors as nano-analytical tools for COVID-19 detection,” Sensors, vol. 21, no. 23, p. 7823, Nov. 2021, doi: 10.3390/s21237823.

J. Qin, L. Liu, H. Shen, and D. Hu, “Uniform pooling for graph networks,” Applied Sciences, vol. 10, no. 18, p. 6287, Sep. 2020, doi: 10.3390/app10186287.

C. Wiecher et al., “Model-based analysis and specification of functional requirements and tests for complex automotive systems,” Systems Engineering, vol. 27, no. 4, pp. 728–744, Jul. 2024, doi: 10.1002/sys.21748.

K. M. Habibullah, G. Gay, and J. Horkoff, “Non-functional requirements for machine learning,” Requirements Engineering, vol. 28, no. 2, pp. 283–316, Jun. 2023, doi: 10.1007/s00766-022-00395-3.

Q. Li and Z. Song, “Ensemble-learning-based prediction of steel bridge deck defect condition,” Applied Sciences, vol. 12, no. 11, p. 5442, May 2022, doi: 10.3390/app12115442.

G. A. Stelea, L. Sangeorzan, and N. Enache-David, “When cybersecurity meets accessibility: A holistic development architecture for inclusive cyber-secure web applications,” Future Internet, vol. 17, no. 2, p. 67, Feb. 2025, doi: 10.3390/fi17020067.

Published
2025-12-10
Abstract views: 31 times
Download PDF: 17 times
How to Cite
Aufan, A., Purwadi, P., & Pritama, A. (2025). Web Information System for E-Sport Arena Community with OWASP-Based Cybersecurity Using XP Method. Journal of Information Systems and Informatics, 7(4), 3379-3406. https://doi.org/10.63158/journalisi.v7i4.1344
Section
Articles