User Satisfaction Analysis of the e-Semesta Application at UIN Syarif Hidayatullah Jakarta Using the Technology Acceptance Model (TAM)

Authors

Keywords:

Technology Acceptance Model, Word Frequency Analysis, Digital Transformation, User Satisfaction

Abstract

As a result of the digital transformation implemented in the higher education setting, UIN Syarif Hidayatullah Jakarta developed the comprehensive, all-in-one academic information system in the form of e-Semesta application. However, high functionality does not necessarily imply high satisfaction from end users of the software. This research models the direct influence of perceived usefulness and perceived ease of use on user satisfaction within the context of the e-Semesta application. Deploying a mixed-methods design, this study gathered survey data from 397 institutional stakeholders, comprising students, lecturers, and administrative staff utilizing purposive convenience sampling. Quantitative responses were evaluated via multiple linear regression, while qualitative feedback underwent word frequency analysis. The novel methodological approach were utilized to rapidly and objectively isolate specific operational bottlenecks. Our analysis demonstrates that PU and PEOU serve as robust predictors of user satisfaction. Whether evaluated individually or through joint estimation, both constructs positively influence the outcome, explaining 88.6% of the variance in satisfaction scores. However, this high explanatory power must be contextualized, as it is partially amplified by Common Method Bias and the sampling method used. Despite the strong predictive metrics, the level of user satisfaction remains at a moderate level. The qualitative analysis reveals the primary obstacles are issues within the back-end server infrastructure, such as login failures and slow networks, despite the high level of both PU and PEOU. Therefore, the institution should improve the back-end infrastructure of the application before focusing on enhancing other functionalities.

References

[1] V. Dhameria, A. I. M. Muazeib, K. M. S. Blhaj, S. Sugiyarsih, and R. A. Rosadah, “The Impact of Digital Transformation in Higher Education Management: Integrating Online Learning and Educational Applications for Efficiency and Accessibility,” Int. J. Educ. Qual. Quant. Res., vol. 4, no. 1, pp. 15–24, Jul. 2025, doi: 10.58418/ijeqqr.v4i1.135.

[2] T. Gkrimpizi, V. Peristeras, and I. Magnisalis, “Classification of Barriers to Digital Transformation in Higher Education Institutions: Systematic Literature Review,” Educ. Sci., vol. 13, no. 7, Jul. 2023, doi: 10.3390/educsci13070746.

[3] A. T. Lee, R. K. Ramasamy, and A. Subbarao, “Understanding Psychosocial Barriers to Healthcare Technology Adoption: A Review of TAM Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology and UTAUT Frameworks,” Healthcare, vol. 13, no. 3, p. 250, Jan. 2025, doi: 10.3390/healthcare13030250.

[4] R. Wandira, A. Fauzi, and F. Nurahim, “Analysis of Factors Influencing Behavioral Intention to Use Cloud-Based Academic Information System Using Extended Technology Acceptance Model (TAM) and Expectation-Confirmation Model (ECM),” J. Inf. Syst. Eng. Bus. Intell., vol. 10, no. 2, pp. 179–190, Jun. 2024, doi: 10.20473/jisebi.10.2.179-190.

[5] S. Sayardoost Tabrizi, A. Sabzian, A. Moeini, and K. Yakideh, “TAM-Based Model for Evaluating Learner Satisfaction of E-Learning Services Case Study: E-Learning System of University of Tehran,” Int. J. Web Res., vol. 6, no. 1, Feb. 2023, doi: 10.22133/ijwr.2024.415953.1178.

[6] T. M. Swe and S. Yang, “Factors Influencing User Satisfaction with University Library Websites in Myanmar,” J. Inf. Sci. Theory Pract., vol. 12, no. 2, pp. 1–21, Jun. 2024, doi: 10.1633/JISTAP.2024.12.2.1.

[7] J. Golzar, S. Noor, and O. Tajik, “Convenience Sampling,” Int. J. Educ. Lang. Stud., vol. 1, no. 2, pp. 72–77, Dec. 2022, doi: 10.22034/ijels.2022.162981.

[8] B. H. Mukti, “Sample size determination: Principles and applications for health research,” Health Sci. Int. J., vol. 3, no. 1, pp. 127–143, Feb. 2025, doi: 10.71357/hsij.v3i1.63.

[9] A. C. Praniffa, T. K. Ahsyar, M. Jazman, Syaifullah, and A. Marsal, “User Satisfaction Analysis using EUCS and TAM Methods of Public Digital Library Application,” Indones. J. Comput. Sci., vol. 14, no. 1, Feb. 2025, doi: 10.33022/ijcs.v14i1.4604.

[10] A. Nabila and M. Waluyo, “User Satisfaction Analysis of QPON Indonesia Using TAM-IPA: Analisis Kepuasan Pengguna Aplikasi QPON Indonesia Menggunakan TAM-IPA,” Acad. Open, vol. 11, no. 1, p. 10.21070/acopen.11.2026.14016-10.21070/acopen.11.2026.14016, May 2026, doi: 10.21070/acopen.11.2026.14016.

[11] R. Suhartini, Ekohariadi, L. Nurlaela, U. Wahyuningsih, Yulistiana, and Y. I. Prihatina, “Validity, Reliability, Intra-rater Instrument Parameter Teaching Factory and Learning Outcomes of Industrial Clothing,” presented at the International Joint Conference on Arts and Humanities 2021 (IJCAH 2021), Atlantis Press, Jan. 2021, pp. 1230–1239. doi: 10.2991/assehr.k.211223.214.

[12] G. Mardiatmoko, “The Application of the Classical Assumption Test in Multiple Linear Regression Analysis (a Case Study of the Preparation of the Allometric Equations of Young Makila),” JTAM J. Teori Dan Apl. Mat., vol. 8, no. 3, pp. 724–739, Jul. 2024, doi: 10.31764/jtam.v8i3.22179.

[13] P. Anandhi and Dr. E. Nathiya, “Application of linear regression with their advantages, disadvantages, assumption and limitations,” Int. J. Stat. Appl. Math., vol. 8, no. 6, pp. 133–137, Nov. 2023, doi: 10.22271/maths.2023.v8.i6b.1463.

[14] L.-C. Chen, “An extended TF-IDF method for improving keyword extraction in traditional corpus-based research: An example of a climate change corpus,” Data Knowl. Eng., vol. 153, p. 102322, Sep. 2024, doi: 10.1016/j.datak.2024.102322.

[15] A. Alluhaybi, K. Usher, J. Durkin, and A. Wilson, “Clinical nurse managers’ leadership styles and staff nurses’ work engagement in Saudi Arabia: A cross-sectional study,” PLOS ONE, vol. 19, no. 3, p. e0296082, Mar. 2024, doi: 10.1371/journal.pone.0296082.

[16] H. K. S. Aljader, “Measuring the Effect of E-Learning Information Quality on Student’s Satisfaction Using the Technology Acceptance Model,” JOIV Int. J. Inform. Vis., vol. 7, no. 3, pp. 878–885, 2023, doi: http://dx.doi.org/10.30630/joiv.7.3.1633.

[17] S. H. Alshammari and E. Babu, “The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT,” Sci. Rep., vol. 15, no. 1, p. 7169, Feb. 2025, doi: 10.1038/s41598-025-91634-4.

[18] R. D. Agustyas, E. H. Kurniawan, and I. Sulistyanto, “USER EXPERIENCE OF LMS UNISKA AS AN E-LEARNING PLATFORM WITH THE TAM METHOD,” J. Pendidik. Bhs. Ingg. Profic., vol. 6, no. 2, p. 237, Jul. 2024, doi: 10.32503/proficiency.v6i2.5354.

[19] C. Chunlei, A. H. B. Jantan, and A. Mohammadi, “The Intervening Role of Perceived Ease of Use and Perceived Usefulness on the relationship between Information Quality, System Quality, Service Quality and Building Information Model（BIM) User Satisfaction in China,” J. Int. Bus. Manag., vol. 6, no. 12, pp. 1–12, Dec. 2023, doi: 10.37227/JIBM-2023-11-6298.

[20] P. Netinant, S. Pukdesree, and M. Rukhiran, “Bridging System Development Perspectives and Quantitative Analysis of User Adoption in Educational Information Systems,” IEEE Access, vol. 13, pp. 172987–173015, 2025, doi: 10.1109/ACCESS.2025.3616630.

[21] I. F. Rachmi, F. R. Asta, and N. D. Kartiko, “The Effects of Perceived Ease of Use, Perceived Usefulness, and Computer Self-Efficacy on e-Nofa Application User Satisfaction,” E3S Web Conf., vol. 388, p. 04017, 2023, doi: 10.1051/e3sconf/202338804017.

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2026-09-29

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