Jurnal Teknologi Informasi dan Multimedia
Vol. 7 No. 4 (2025): November

Enhancing Governance: Evaluating E-Government Service Quality and Recommendations for Improvement in Suket Kepuharjo Sub-District

Husin, Husin (Unknown)
Hakim, Lukman (Unknown)
Huda, Choirul (Unknown)



Article Info

Publish Date
23 Oct 2025

Abstract

This study evaluates the quality of e-government services in Suket Kepuharjo Sub-District using the E-GOVQUAL framework and the Importance Performance Analysis (IPA) approach. The framework includes six dimensions: ease of use, trust, functionality, reliability, content, and citizen support. Data were collected through a structured questionnaire distributed to 37 respondents, with all variables meeting validity and reliability thresholds. The results showed a mean performance score of 3.45, slightly higher than the mean importance score of 3.42, resulting in an overall average gap of +0.014. Attributes with strong performance included secure data storage (gap = +0.29), clear website structure (gap = +0.08), and help page availability (gap = +0.19). However, several critical weaknesses were identified in Quadrant I, such as user ability to navigate the website (gap = -0.38), service responsiveness (gap = -0.25), information accuracy (gap = -0.25), and application compatibility across devices (gap = -0.15). These findings indicate that while e-government services moderately meet user expectations, there remains significant room for improvement, especially in usability, responsiveness, and information reliability. The integration of E-GOVQUAL and IPA offers a comprehensive and user-centred framework to guide systematic enhancements in digital public services.

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Journal Info

Abbrev

jtim

Publisher

Subject

Computer Science & IT

Description

Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, ...