User Satisfaction Analysis on the Quality of Lapisbogor.co.id Website using the Webqual 4.0 Method

Authors

  • Moses Aripin Indah Setiawan Universitas Bina Sarana Informatika
  • Kudiantoro Widianto Universitas Bina Sarana Informatika
  • Syaifur Rahmatullah AR Universitas Nusa Mandiri
  • M. Iqbal Alifudin Universitas Bina Sarana Informatika
  • Irmawati Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.59934/jaiea.v5i1.1797

Keywords:

WEBQUAL 4.0, Lapis Bogor Sangkuriang, User Satisfaction

Abstract

Website quality is a vital element for the sustainability and customer satisfaction within the digital business landscape, especially for prominent brands like Lapis Bogor Sangkuriang that rely on an online presence. This study was designed to investigate the impact of website quality, measured by WebQual 4.0 (encompassing Usability Quality, Information Quality, and Service Interaction Quality), on user satisfaction with the lapisbogor.co.id website. A quantitative approach was applied through the dissemination of questionnaires to 150 respondents who are users of the Lapis Bogor Sangkuriang website. Regression analysis results indicate that all three WebQual 4.0 dimensions collectively have a significant influence on user satisfaction. This finding suggests that the website quality of Lapis Bogor Sangkuriang has successfully met user expectations, with website quality variables contributing approximately 58% to the perceived satisfaction level. Therefore, this research recommends that Lapis Bogor Sangkuriang continue to invest in monitoring and improving its website quality. Continuous efforts in optimizing the WebQual 4.0 dimensions will be crucial for maintaining a positive user experience and strengthening the company's competitive position in the market.

 

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Published

2025-10-15

How to Cite

Moses Aripin Indah Setiawan, Kudiantoro Widianto, Syaifur Rahmatullah AR, M. Iqbal Alifudin, & Irmawati. (2025). User Satisfaction Analysis on the Quality of Lapisbogor.co.id Website using the Webqual 4.0 Method. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 5(1), 2049–2057. https://doi.org/10.59934/jaiea.v5i1.1797