EXAMINING THE TECHNOLOGY ACCEPTANCE MODEL IN THE ADOPTION OF NARCOTIC PRECURSOR REPORTING SYSTEM (SIPPRE)

Retno Agus Setiawan(1), Peppy Oktaviani(2),


(1) Department of Information System, Harapan Bangsa University, Purwokerto, Central Java
(2) Department of Information System, Harapan Bangsa University, Purwokerto, Central Java
Corresponding Author

Abstract


The use of Information and Communication Technology (ICT) among pharmacy professionals is increasing. Narcotic Precursor Reporting System (SIPPRE) is one of these technologies and can be used to supervise the distribution of narcotic precursors. The aim of this study is to investigate the predicting factors that influence the intention to use SIPPRE among pharmacy professionals. The Technology Acceptance Model (TAM) was used to shape the theoretical foundation for this study comprising perceived usefulness, perceived ease of use, attitude toward use, and intention to use. A quantitative approach was applied, using a five-point Likert scale questionnaire, adapted from previous studies. The participants for this study comprised 157 pharmacy professionals. The Results obtained using structural equation modeling indicated that pharmacy professionals perceived SIPPRE as an easy to use and useful system, and they favored its use in the future. In addition, perceived ease of use and usefulness significantly influenced attitudes toward the system. Apart from that, attitude toward use had a positive relationship with intention to use SIPPRE among pharmacy professionals. Surprisingly, perceived usefulness had a negative correlation with an intention to use. Overall, the TAM is a valid model to help explain pharmacy professional's intention to use SIPPRE. The results of this study provided useful insights for healthcare agencies to recognize the key elements that could improve the narcotic precursor reporting management.

 


Keywords


Technology Acceptance Model, Narcotic Precursor Reporting System (SIPPRE), Drug Precursor

References


UNODC, “World Drugs Report 2019,” 2019.

Badan Narkotika Nasional, “PRESS RELEASE AKHIR TAHUN,” 2019.

H. Rustiningsih, “Prekursor Narkotika Psikotropika Mengapa Perlu Diawasi,” Widyaiswara Madya Pusdiklat Bea dan Cukai, 2017.

L. Taskarina, “CLANDESTINE LABORATORY: ANALISIS FAKTOR PENDORONG BERKEMBANGNYA LABORATORIUM GELAP NARKOBA DI INDONESIA DALAM KONTEKS TRANSNATIONAL ORGANIZED CRIMES (TNOCs),” J. Kriminologi Indones., vol. 6, no. 3, pp. 203–215, 2010.

P. Botella, C. Muniesa, V. Vicente, and A. Cabrera-García, “Effect of drug precursor in cell uptake and cytotoxicity of redox-responsive camptothecin nanomedicines,” Mater. Sci. Eng. C, vol. 58, pp. 692–699, Jan. 2016.

D. Bastiar, “Penegakan Hukum terhadap Penyalahgunaan dan Pencegahan Pengguna Narkotika di Indonesia,” J. RECHTENS, vol. 8, no. 2, pp. 209–222, Dec. 2019.

N. A. Pangestika, “Tingkat Pengetahuan Tenaga Kefarmasian dan Evaluasi Pengelolaan Obat Prekursor pada Apotek di Kabupaten Banjarnegara,” Universitas Muhammadiyah Purwokerto, 2018.

Y. L. Sari, “Evaluasi Pengelolaan Obat yang Mengandung Prekursor di Apotek Kota Probolinggo,” Akademi Farmasi Putera Indonesia Malang, 2019.

K. Zheng, R. Padman, M. P. Johnson, and H. S. Diamond, “Evaluation of healthcare IT applications: The user acceptance perspective,” Stud. Comput. Intell., vol. 65, pp. 49–78, 2007.

T. J. Willis, “An Evaluation of the Technology Acceptance Model as a Means of Understanding Online Social Networking Behavior,” in Doctoral dissertation, University of South Florida, 2008.

R. A. Setiawan, D. B. Setyohadi, and Pranowo, “Understanding customers’ intention to use social network sites as complaint channel: an analysis of young customers’ perspectives,” E3S Web Conf., vol. 31, p. 11014, Feb. 2018.

R. A. Setiawan and P. Octaviany, Manual Book: Aplikasi Sistem Informasi Pelaporan Penggunaan Sediaan Jadi Prekursor dan Obat-obatan Tertentu. LPPM Universitas Harapan Bangsa, 2020.

D. Kwok and S. Yang, “Evaluating the intention to use ICT collaborative tools in a social constructivist environment,” Int. J. Educ. Technol. High. Educ., vol. 14, no. 1, 2017.

Y. H. P. Iskandar, G. Subramaniam, M. I. A. Majid, A. M. Ariff, and G. K. L. Rao, “Predicting healthcare professionals’ intention to use poison information system in a Malaysian public hospital,” Heal. Inf. Sci. Syst., vol. 8, no. 1, p. 6, Dec. 2020.

A. Sadik, “Students’ acceptance of file sharing systems as a tool for sharing course materials: The case of Google Drive,” Educ. Inf. Technol., vol. 22, no. 5, pp. 2455–2470, 2017.

ISO 9241, “Ergonomics of human-system interaction — Part 11: Usability: Definitions and concepts,” 2018.

F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, pp. 319–340, 1989.

N. Cobelli, Innovation in Community-Based Private Practices Through eHealth. Cham: Springer International Publishing, 2020.

N. Ernstmann, O. Ommen, M. Neumann, A. Hammer, R. Voltz, and H. Pfaff, “Primary Care Physician’s Attitude Towards the GERMAN e-Health Card Project—Determinants and Implications,” J. Med. Syst., vol. 33, no. 3, pp. 181–188, Jun. 2009.

T. Doleck, P. Bazelais, and D. J. Lemay, “Examining the antecedents of social networking sites use among CEGEP students,” Educ. Inf. Technol., vol. 22, no. 5, pp. 2103–2123, 2017.

W. Chin, “The partial least squares approach for structural equation modeling,” in Methodology for business and management, Lawrence Erlbaum Associates Publishers, 1998, pp. 295–336.

J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis, 7th ed. Upper Saddle: Prentice-Hall, 2009.

J. Nunnally, Psychometric theory, 2nd ed. New York, NY: McGraw-Hill, 1978.

J. F. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, Multivariate Data Analysis with Readings, 4th ed. Englewood Cliffs: Prentice-Hall, 1995.

H. Baumgartner and C. Homburg, “Applications of structural equation modeling in marketing and consumer research: A review,” Int. J. Res. Mark., vol. 13, no. 2, pp. 139–161, 1996.

J. F. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, Multivariate Data Analysis, 5th ed. Upper Saddle: Prentice-Hall, 1998.

L.-T. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling,” vol. 6, no. 1, pp. 1–55, 1999.

R. P. Bagozzi and Y. Yi, “On the Evaluation of Structural Equation Models,” J. Acad. Mark. Sci., vol. 16, no. 1, pp. 74–94, 1988.


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