Analisis Kesediaan User Permission pada Fitur App Tracking Transparency melalui pendekatan Protection Motivation Theory
Kata Kunci:
Protection motivation theory, privasi, pengguna, behaviour, iOS, Generalized Linear ModelAbstrak
App Tracking Transparency merupakan fitur iOS yang memberikan kebebasan pengguna dalam mengizinkan aplikasi untuk memantau aktivitas dan privasi. Dengan fitur ini, banyak pengguna yang menolak untuk memberikan izin sehingga timbul fenomena dimana kian sedikitnya data dan informasi yang diperoleh pengembang sehingga menyebabkan kesulitan dalam menargetkan iklan. Fenomena ini berkaitan dengan Protection Motivation Theory yang merupakan teori perilaku motivasi seseorang dalam memproteksi diri. Penelitian ini bertujuan untuk mengetahui faktor yang mempengaruhi keputusan pengguna dalam perizinan App Tracking Transparency. Penelitian ini akan didasarkan pada Protection Motivation Theory, yang mencakup Perceived Threats Severity, Perceived Threats Vulnerability, dan Gender. Penelitian ini melibatkan 97 mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Data akan dianalisis menggunakan Generalized Linear Model dengan tujuan mengevaluasi pengaruh variabel independen terhadap dependen yang digunakan. Analisis tambahan berupa pengujian Kruskal-Wallis dilakukan guna memperoleh informasi lebih dalam. Hasil analisis menunjukkan bahwa hanya variabel Perceived Threats Severity yang berdampak signifikan dan negatif terhadap keputusan pengguna dalam perizinan App Tracking Transparency.
Referensi
Barth, S., & de Jong, M. D. T. (2017). The privacy paradox – Investigating discrepancies between expressed privacy concerns and actual online behavior – A systematic literature review. Telematics and Informatics, 34(7), 1038–1058. https://doi.org/10.1016/j.tele.2017.04.013
Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2021). Exploring Motivations for Online Privacy Protection Behavior: Insights From Panel Data. Communication Research, 48(7), 953–977. https://doi.org/10.1177/0093650218800915
Marikyan, D., & Papagiannidis, S. (2023). Protection Motivation Theory: A Review (S. Papagiannidis). TheoryHub Book. https://open.ncl.ac.uk/theories/10/protection-motivation-theory/
Mishra, P., Pandey, C., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.ACA_157_18
Mohamed, N., & Ahmad, I. H. (2012). Information privacy concerns, antecedents and privacy measure use in social networking sites: Evidence from Malaysia. Computers in Human Behavior, 28(6), 2366–2375. https://doi.org/10.1016/j.chb.2012.07.008
Park, Y. J. (2015). Do men and women differ in privacy? Gendered privacy and (in)equality in the Internet. Computers in Human Behavior, 50, 252–258. https://doi.org/10.1016/j.chb.2015.04.011
Statcounter Global Stats. (2023). Mobile Operating System Market Share Indonesia. https://gs.statcounter.com/os-market-share/mobile/indonesia
Sugiyono. (2017). Metode penelitian kuantitatif, kualitatif, dan R&D (1st ed.). ALFABETA.
Wang, J., Liu-Lastres, B., Ritchie, B. W., & Mills, D. J. (2019). Travellers’ self-protections against health risks: An application of the full Protection Motivation Theory. Annals of Tourism Research, 78, 102743. https://doi.org/10.1016/j.annals.2019.102743
Barth, S., & de Jong, M. D. T. (2017). The privacy paradox – Investigating discrepancies between expressed privacy concerns and actual online behavior – A systematic literature review. Telematics and Informatics, 34(7), 1038–1058. https://doi.org/10.1016/j.tele.2017.04.013
Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2021). Exploring Motivations for Online Privacy Protection Behavior: Insights From Panel Data. Communication Research, 48(7), 953–977. https://doi.org/10.1177/0093650218800915
Marikyan, D., & Papagiannidis, S. (2023). Protection Motivation Theory: A Review (S. Papagiannidis). TheoryHub Book. https://open.ncl.ac.uk/theories/10/protection-motivation-theory/
Mishra, P., Pandey, C., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.ACA_157_18
Mohamed, N., & Ahmad, I. H. (2012). Information privacy concerns, antecedents and privacy measure use in social networking sites: Evidence from Malaysia. Computers in Human Behavior, 28(6), 2366–2375. https://doi.org/10.1016/j.chb.2012.07.008
Park, Y. J. (2015). Do men and women differ in privacy? Gendered privacy and (in)equality in the Internet. Computers in Human Behavior, 50, 252–258. https://doi.org/10.1016/j.chb.2015.04.011
Statcounter Global Stats. (2023). Mobile Operating System Market Share Indonesia. https://gs.statcounter.com/os-market-share/mobile/indonesia
Sugiyono. (2017). Metode penelitian kuantitatif, kualitatif, dan R&D (1st ed.). ALFABETA.
Wang, J., Liu-Lastres, B., Ritchie, B. W., & Mills, D. J. (2019). Travellers’ self-protections against health risks: An application of the full Protection Motivation Theory. Annals of Tourism Research, 78, 102743. https://doi.org/10.1016/j.annals.2019.102743
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