The effect of using the SIDONI application on increasing the number of blood donors at the Blood Transfusion Unit of the Indonesian Red Cross, Tangerang Regency
Main Article Content
Keywords
SIDONI, Digital Health Application, Blood Donation, Donor Participation, PLS-SEM, Technology Acceptance, Indonesia
Abstract
Background: Blood donation depends on voluntary public participation, which is influenced by awareness, access to information, and ease of engagement with blood transfusion services. Digital health applications may reduce barriers to donor participation; however, empirical evidence from Indonesia on the association between donor application use and donation behavior remains limited. This study aims to examine the association between the Sistem Informasi Donor Darah Indonesia (SIDONI) application and blood donor participation at the Blood Transfusion Unit (BTU) of the Indonesian Red Cross Society (IRCS), Tangerang Regency, Indonesia.
Methods: A quantitative cross-sectional design was used. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to evaluate the measurement model and structural model properties. One hundred active SIDONI users were recruited through purposive sampling from a total registered user population of 194,274. Inclusion required at least one blood donation in the preceding six months. A self-administered 5-point Likert scale questionnaire was developed based on the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). The independent latent construct (X) represented SIDONI application use; the dependent latent construct (Y) represented blood donor participation.
Results: The measurement model demonstrated acceptable reliability (Cronbach's alpha: X = 0.968, Y = 0.933; composite reliability: X = 0.972, Y = 0.943) and convergent validity (AVE: X = 0.716, Y = 0.629). Discriminant validity was supported by HTMT = 0.871, with a 95% bootstrapped confidence interval of 0.781–0.935, which did not include 1.0. Four indicators showed outer loadings below 0.70 (X03 = 0.584, Y01 = 0.610, Y08 = 0.635, Y07 = 0.701). The structural model yielded a path coefficient of β = 0.850 (95% CI: 0.774–0.912), and R² = 0.723, indicating a strong positive association between SIDONI use and donor participation within this sample. VIF = 1.0 indicated no multicollinearity concern.
Conclusion: SIDONI application use was strongly and positively associated with blood donor participation among active users in Tangerang Regency.
References
2. Kementerian Kesehatan Republik Indonesia. Infodatin: situasi donor darah di Indonesia. Jakarta: Kemenkes RI; 2020.
3. Davey RJ. Recruiting blood donors: challenges and opportunities. Transfusion. 2004;44(4):597–600. doi:10.1111/j.0041-1132.2004.04402.x.
4. Shinta S, Hartini WM, Safitri MR. Pengaruh penyuluhan donor darah terhadap minat donor darah pada siswa SMKN 3 Selong tahun 2022. Jurnal Ilmu Kedokteran dan Kesehatan Indonesia. 2022;2(3):140–154. doi:10.55606/jikki.v2i3.842.
5. Fauzi A, Supadmi FRS, Mumpuni N. Perbandingan jumlah donasi darah sebelum dan saat pandemi Covid-19 di BTU IRCS Banyumas tahun 2019 dan 2020. Jurnal Surya Medika. 2021;7(1):227–232. doi:10.33084/jsm.v7i1.2372.
6. Sari AF, Husodo AH, Lazuardi L. Sikap mahasiswa terhadap pesan pengingat donor darah dengan teknologi SMS gateway. Jurnal Berkala Kesehatan. 2016;1(1):21-27. doi: 10.20527/jbk.v1i1.656.
7. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989;13(3):319–339. doi: 10.2307/249008.
8. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Quarterly. 2003;27(3):425–478. doi: 10.2307/30036540.
9. Bednall TC, Bove LL. Donating blood: a meta-analytic review of self-reported motivators and deterrents. Transfus Med Rev. 2011;25(4):317–334. doi: 10.1016/j.tmrv.2011.04.005.
10. Hair JF, Hult GTM, Ringle CM, Sarstedt M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 3rd ed. Thousand Oaks, CA: SAGE Publications; 2022.
11. Astuti Y, Artini D. Hubungan komunikasi efektif dengan kepuasan pendonor darah dalam pelayanan seleksi donor di Unit Transfusi Darah PMI Kota Yogyakarta. Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan. 2020;3(3):160–167. doi:10.22435/jpppk.v3i3.2737.
12. Iqbal M, Faqih H, Nugroho BYS, Rizqulloh L, Puspitasari A. Gambaran penerimaan pasien terhadap penggunaan aplikasi pustaka dengan metode UTAUT 2 di Puskesmas terakreditasi paripurna Kota Semarang. VISIKES: Jurnal Kesehatan Masyarakat. 2022;21(2):518-527. doi:10.33633/visikes.v21i2Supp.6314.
13. Shofwan I, Witcahyo E, Herawati YT. Analisis kesiapan pengguna dan pengaruhnya terhadap penerimaan SIK Lumajang sebagai sistem informasi manajemen puskesmas. Jurnal Kedokteran dan Kesehatan. 2018;14(1):83–97. doi:10.24853/jkk.14.1.83-97.
14. Dewi MIS, Rosyidah RA, Hartini WM. Hubungan antara tingkat pengetahuan dengan minat donor darah di masa pandemi Covid-19 pada anggota Polres Nagekeo. Jurnal Riset Rumpun Ilmu Kedokteran. 2022;1(2):61–76. doi:10.55606/jurrike.v1i2.542.
15. Sinungan NP, Darma GS. Faktor-faktor pendukung penggunaan antrean online dalam menunjang peningkatan mutu layanan bagi BPJS Kesehatan Kedeputian Wilayah XI. E-Jurnal Ekonomi dan Bisnis Universitas Udayana. 2023;12(11):2245. doi:10.24843/EEB.2023.v12.i11.p13.
16. Syafiqah SA, Parumpu FA, Hardani R. Analisis TAM (Technology Acceptance Model) aplikasi Medscape® pada mahasiswa jurusan farmasi Universitas Tadulako. PREPOTIF: Jurnal Kesehatan Masyarakat. 2022;6(2):1776–1781. doi:10.31004/prepotif.v6i2.5229.