PENGUKURAN KESIAPAN IMPLEMENTASI TEKNOLOGI HYPER-CONVERGED INFRASTRUCTURE DI RUMAH SAKIT BANDUNG RAYA BERDASARKAN MODEL TRI 2.0 DAN TAM

Authors

  • Tauchida Winanda Fadjar Setiawan Program Studi Sistem Informasi, Fakultas Teknik, Universitas Sangga Buana, Bandung, Indonesia Author
  • Khaerul Manaf Program Studi Sistem Informasi, Fakultas Teknik, Universitas Sangga Buana, Bandung, Indonesia Author
  • Beki Subaeki Program Studi Sistem Informasi, Fakultas Teknik, Universitas Sangga Buana, Bandung, Indonesia Author
  • Raden Muhammad Adrian Septiandry Program Studi Sistem Informasi, Fakultas Teknik, Universitas Sangga Buana, Bandung, Indonesia Author
  • Yanyan Gunawan Program Studi Sistem Informasi, Fakultas Teknik, Universitas Sangga Buana, Bandung, Indonesia Author

DOI:

https://doi.org/10.71282/at-taklim.v2i8.888

Keywords:

Hyper-Converged Infrastructure, Technology, Data Center

Abstract

Efficient information technology management has become a primary necessity for hospitals. One emerging solution is Hyper-Converged Infrastructure (HCI), which integrates computing, storage, and networking into a single platform. This study aims to assess the readiness of hospitals in the Bandung Raya region to adopt HCI, using the Technology Readiness Index (TRI) 2.0 and the Technology Acceptance Model (TAM) as the analytical framework. TRI 2.0 encompasses four psychological dimensions: optimism, innovativeness, discomfort, and insecurity. TAM is employed to evaluate perceived ease of use and perceived usefulness of the technology. The research method is quantitative, utilizing a questionnaire survey distributed to IT personnel and hospital management. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that optimism and innovativeness positively influence technology perception, while discomfort and insecurity act as psychological barriers. Positive perceptions of ease of use and usefulness further enhance readiness for HCI implementation.

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References

Abbasi, A. A., Abbasi, A., Shamshirband, S., Chronopoulos, A. T., Persico, V., & Pescape, A. (2019). Software-Defined Cloud Computing: A Systematic Review on Latest Trends and Developments. IEEE Access, 7, 93294–93314. doi: 10.1109/ACCESS.2019.2927822.

Andrian Syahputra, Ragil Wiranti, & Widiya Astita, W. A. (2022). PERAN SISTEM INFORMASI MANAJEMEN ORGANISASI DALAM PENGAMBILAN KEPUTUSAN. Jurnal Manajemen Sistem Informasi (JMASIF), 1(1), 26–31. doi: 10.35870/jmasif.v1i1.67.

Apa itu infrastruktur hiperkonvergen? | IBM. (n.d.). Retrieved from https://www.ibm.com/id-id/topics/hyperconverged-infrastructure?form=MG0AV3.

Azeem, S. A., & Sharma, S. K. (2017). Study of Converged Infrastructure & Hyper Converge Infrastructre As Future of Data Centre. International Journal of Advanced Research in Computer Science, 8(5), 900–903. doi: 10.26483/IJARCS.V8I5.3476.

Buyya, R., Calheiros, R. N., & Li, X. (2012). Autonomic Cloud computing: Open challenges and architectural elements. Proceedings - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012, 3–10. doi: 10.1109/EAIT.2012.6407847.

Cao, K., Liu, Y., Meng, G., & Sun, Q. (2020). An Overview on Edge Computing Research. IEEE Access, PP, 1. doi: 10.1109/ACCESS.2020.2991734.

Cheah, J. H., Magno, F., & Cassia, F. (2024). Reviewing the SmartPLS 4 software: the latest features and enhancements. Journal of Marketing Analytics, 12(1), 97–107. doi: 10.1057/S41270-023-00266-Y/METRICS.

Damayanti, R. M., Pramesti, D., Ayuninggar, L., Martini, E., & Rosdaliva, M. (2022). Readiness for Digital Financial Transformation: The Case of Micro, Small and Medium Enterprises in Indonesia. International Journal of Economics and Management, 19(1), 57–66. doi: 10.1234/ijem.v19i1.2022.

Darmawan, A. K., Setyawan, M. B., Waail, M., & Wajieh, A. (2022). Predicting Smart Regency Readiness on Sub-Urban Area in Indonesia: A perspective of Technology Readiness Index 2.0; Predicting Smart Regency Readiness on Sub-Urban Area in Indonesia: A perspective of Technology Readiness Index 2.0. 2022 International Conference on ICT for Smart Society (ICISS). doi: 10.1109/ICISS55894.2022.9915246.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. doi: 10.2307/249008.

Dawod, A., Abdullah, N. I., & Al-Ani, A. D. (2019). Software Defined Networks Challenges and Future Direction of Research Article in. International Journal of Research, January. Retrieved from https://www.researchgate.net/publication/330599431.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Evaluation of Formative Measurement Models. doi: 10.1007/978-3-030-80519-7_5.

Hair, J. F., Hult, G. T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) - Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, Marko Sarstedt. Sage, 374.

Hong, J., & Kim, S. (2022). Technology Readiness and Organizational Adoption of Smart Hospital Systems: Evidence from Korea. Journal of Medical Systems, 46(3), 1–15. doi: 10.1007/s10916-022-01876-9.

Hwang, H., & Park, M. (2020). TRI 2.0 Assessment for Public Sector Digitalization: A Structural Equation Modeling Approach. Technological Forecasting and Social Change, 158, 120–134. doi: 10.1016/j.techfore.2020.120134.

Iskandar, R., Puspita, M., & Haryanto, R. (2020). Pengembangan infrastruktur jaringan berbasis Software Defined Networking (SDN) untuk meningkatkan efisiensi jaringan pada perusahaan. Jurnal Teknologi Dan Sistem Komputer, 8(2), 99–110.

John, D., Peterson, L., & Williams, K. (2020). The role of Hyper-Converged Infrastructure in hospital data management. Healthcare IT Journal, 18(4), 234–245.

Joseph, S., Herold, M., Sunderlin, W. D., -, al, Suryanti, S., Sutaji, D., Nusantara, T., Mohamed Yosser, I., Zulkarnain Bin Syed Idrus, S., & Ali Elmetwaly Ali, A. (2020). Technology Readiness Index 2.0 as Predictors of E-Health Readiness among Potential Users: A Case of Conflict Regions in Libya The Development of Model for Measuring Railway Wheels Manufacturing Readiness Level Iwan Inrawan Wiratmadja and Anas Mufid-An Assessment of Teachers’ Readiness for Online Teaching Technology Readiness Index 2.0 as Predictors of E-Health Readiness among Potential Users: A Case of Conflict Regions in Libya. Journal of Physics: Conference Series, 1529, 32009. doi: 10.1088/1742-6596/1529/3/032009.

Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert Scale: Explored and Explained. British Journal of Applied Science & Technology, 7(4), 396–403. doi: 10.9734/BJAST/2015/14975.

Kaur, N., & Sood, S. K. (2017). An Energy-Efficient Architecture for the Internet of Things (IoT). IEEE Systems Journal, 11(2), 796–805. doi: 10.1109/JSYST.2015.2469676.

Khairunnisa, P. A., Annisa, N., & Parhusip, J. (2024). Penerapan Teknologi SDN ( Software-Defined Networking ) untuk Meningkatkan Keamanan Jaringan Perusahaan. 4, 2–9.

Lambropoulos, G., Mitropoulos, S., & Douligeris, C. (2021). Improving business performance by employing virtualization technology: A case study in the financial sector. Computers, 10(4), 1–20. doi: 10.3390/computers10040052

Laudon, K. C. ., & Laudon, J. P. . (2014). Management information systems : managing the digital firm. Pearson Education.

Memon, M. A., Ramayah, T., Cheah, J. H., Ting, H., Chuah, F., & Cham, T. H. (2021). PLS-SEM STATISTICAL PROGRAMS: A REVIEW. Journal of Applied Structural Equation Modeling, 5(1), i–xiv. doi: 10.47263/JASEM.5(1)06.

Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307-320. doi: 10.1177/109467050024001.

Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. doi: 10.1177/1094670514539730.

Patel D, Shah A, & Gupta R. (2022). Adoption of Hyper-Converged Infrastructure in Healthcare Organizations. Journal of Information Systems, 112–130.

Pogarcic, I., Krnjak, D., & Ozanic, D. (2012). Business benefits from the virtualization of an ICT infrastructure. International Journal of Engineering Business Management, 4(1), 1–8. doi: 10.5772/51603.

Rao, K., Ramakrishna, K., & Naik, M. (2020). Emerging trends in hyperconverged infrastructure. International Journal of Computer Applications, 182(32), 15–21.

Rizaldi, Y., & Santoso, A. (2021). Pengaruh Technology Readiness dan Perceived Usefulness terhadap Penerimaan Sistem Informasi Kesehatan. Jurnal Sistem Informasi Dan Teknologi, 9(2), 101–112.

Sari, D. P., Sumantri, M. S., & Hidayat, W. (2022). Perbandingan Hasil Analisis Data Menggunakan WarpPLS, SmartPLS, Amos, dan SPSS pada Penelitian Teknologi Pendidikan. Jurnal Teknologi Pembelajaran Indonesia, 9(1), 1–10. doi: 10.23887/jurnal_tp.v9i1.3424.

Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. doi: 10.1108/EJM-02-2019-0189.

Silva-Atencio, G., & Umaña-Ramírez, M. (2023). The evolution and trends of hyperconvergence in the telecommunications sector: a competitive intelligence review. DYNA (Colombia), 90(227), 126–132. doi: 10.15446/DYNA.V90N227.107360.

Singh Gill, S. (n.d.). Autonomic Cloud Computing: Research Perspective. Retrieved from https://orcid.org/0000-0002-3913-0369.

Smith, A., Lin, C., & Rodriguez, M. (2023). Efficiency gains through Hyper-Converged Infrastructure in hospitals: A global perspective. Global Health Technology Journal, 22(5), 456–472.

Subchiawan, M., & Rahmawati, D. (n.d.). META-ANALISIS PENELITIAN TECHNOLOGY READINESS DI INDONESIA.

Subiyakto, A., Ahlan, A. R., Kartiwi, M., & Sukmana, H. T. (2015). Measurement of information system project success based on perceptions of the internal stakeholders. International Journal of Electrical and Computer Engineering, 5(2), 271–279. doi: 10.11591/ijece.v5i2.pp271-279.

Sugiyono. (2020). Metodologi Penelitian Kuantitatif, Kualitatif dan R & D.

Vishesh, E. R., & Pamadi, N. (2023). Effective Resource Management In Virtualized Environments. JETNR.ORG JETNR2307001 Journal of Emerging Trends and Novel Research, 1(7), 2984–9276. Retrieved from www.jetnr.org.

Wang, L., Tao, J., Kunze, M., Castellanos, A. C., Kramer, D., & Karl, W. (2008). Scientific Cloud Computing: Early Definition and Experience. 2008 10th IEEE International Conference on High Performance Computing and Communications, 825–830. doi: 10.1109/HPCC.2008.38.

What is Hyper-Converged Infrastructure? The Ultimate Guide. (n.d.). Retrieved from https://e.huawei.com/en/knowledge/2024/solutions/storage/what-is-hyper-converged-infrastructure?form=MG0AV3.

Xie, Z. (2023). Data Center Based on Cloud Computing Technology. IJIIS: International Journal of Informatics and Information Systems, 6(1), 31–37. doi: 10.47738/IJIIS.V6I1.128.

Yamin, S., & Kurniawan, H. (2011). Generasi Baru Mengolah Data Penelitian dengan Partial Least Square Path Modeling: Aplikasi dengan Software XLSTAT, SmartPLS, dan Visual PLS. Jakarta: Salemba Infotek.

Younge, A. J., Von Laszewski, G., Wang, L., Lopez-Alarcon, S., & Carithers, W. (2010). Efficient resource management for cloud computing environments. 2010 International Conference on Green Computing, Green Comp 2010, 357–364. doi: 10.1109/GREENCOMP.2010.5598294.

Zhang, L., & Chen, Y. (2019). Advancements in software-defined data center technologies. Journal of Cloud Computing, 8(1), 12–22.

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Published

29-08-2025

How to Cite

PENGUKURAN KESIAPAN IMPLEMENTASI TEKNOLOGI HYPER-CONVERGED INFRASTRUCTURE DI RUMAH SAKIT BANDUNG RAYA BERDASARKAN MODEL TRI 2.0 DAN TAM. (2025). AT-TAKLIM: Jurnal Pendidikan Multidisiplin, 2(8), 172-200. https://doi.org/10.71282/at-taklim.v2i8.888

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