THE EFFECT OF PERCEIVED SECURITY ON EMOTIONAL TRUST AND PERFORMANCE IMPACT OF SRIKANDI APPLICATION USERS: A TECHNOLOGY ACCEPTANCE MODEL APPROACH

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DOI:

https://doi.org/10.26740/jpap.v14n2.p946-958

Abstract

Phenomenon/Issue: The growing adoption of information technology in public administration emphasizes the need for strong system security to protect data, foster user confidence, and enhance employee performance, especially in the use of e-government applications such as Srikandi.

Purpose: To analyze the influence of perceived security on emotional trust and performance impact of Srikandi application users using the Technology Acceptance Model (TAM) framework.

Novelty:This research integrates perceived security and emotional trust into the TAM framework within an e-government archival system, addressing gaps in prior research, particularly the limited studies in religious-based government institutions and inconsistent findings.

Research Methods: A quantitative approach was employed using Structural Equation Modeling - Generalized Structured Component Analysis (SEM–GSCA) with GSCA Pro software version 1.3.0.0. This study involved 50 employees from Balai Diklat Keagamaan Surabaya as respondents, while the data were obtained using a Likert-scale questionnaire ranging from 1 to 5.

Results: Perceived security positively and significantly affects perceived ease of use, perceived usefulness, and emotional trust. Perceived usefulness significantly affects emotional trust, and emotional trust significantly affects performance impact. Nevertheless, perceived ease of use was found to have no significant influence on emotional trust.

Research Contributions:  This research enriches previous studies related to information systems use in mandatory environments by demonstrating the essential function of perceived security in influencing emotional trust and enhancing performance impact in e-government systems, while emphasizing the importance for developers to maintain system quality, security, and user experience in supporting users’ task performance.

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Published

2026-08-31

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