Brilliance: Research of Artificial Intelligence
Vol. 6 No. 1 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026

Evaluation of Employee Payroll Website Quality Using the WebQual 4.0 Model at SPBU 23.301.34

Olivia, Olivia (Unknown)
Farisi, Ahmad (Unknown)



Article Info

Publish Date
19 Jan 2026

Abstract

The rapid adoption of web-based information systems in human resource management has increased the importance of evaluating website quality from the user perspective. This study aims to evaluate the quality of the employee payroll website at SPBU 23.301.34 using the WebQual 4.0 model, which consists of usability, information quality, and service interaction quality, as well as user satisfaction. A quantitative approach was employed using a descriptive and verificative research design. Data were collected through questionnaires distributed to all active users of the payroll website, totaling 24 respondents, supported by observations and interviews. The collected data were analyzed using descriptive statistics, validity and reliability testing, and mean value analysis for each indicator and dimension. The results indicate that the overall quality of the payroll website is categorized as good. The usability and information quality dimensions obtained the highest mean scores, indicating that the website is easy to use and provides clear, accurate, and understandable payroll information. In contrast, service interaction quality received the lowest score, mainly related to system response speed and occasional technical issues during peak usage periods. Despite these limitations, user satisfaction remained at a moderately satisfied to satisfied level, demonstrating that the website provides practical benefits for employees. These findings suggest that the payroll website contributes to improving transparency and efficiency in payroll administration. However, improvements in system performance, stability, and data update processes are recommended to further enhance user experience and service quality.

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Journal Info

Abbrev

brilliance

Publisher

Subject

Decision Sciences, Operations Research & Management Mathematics Other

Description

Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest ...