Evaluasi Konten Aplikasi Satusehat Menggunakan Mobile Appalication Rating Scale (Mars) dari Prespektif Generasi Z
Article Sidebar
Main Article Content
Abstract
Article Summary
The Covid-19 pandemic is driving the emergence of many new applications in the healthcare field as innovative solutions for safe and effective healthcare services. The increase in smartphone penetration and internet access in Indonesia, especially among Generation Z (born 1995-2010) who are active internet users for more than seven hours per day, supports this trend. This study evaluated the SatuSehat app using the Mobile Application Rating Scale (MARS) measurement tool. The aim was to provide an overview of government healthcare applications. The results review the features of the SatuSehat app and analyze its quality with MARS. This evaluation helps developers design useful and easy-to-use applications to meet the needs of the community in the future. SatuSehat application scored high in Application Quality variables such as Engagement, Functionality, Aesthetics, and Information, with a score of (4.1/5). The success of this application shows that the transformation from PeduliLindungi to SatuSehat has significantly improved its quality. The MARS evaluation shows that generation Z can rely on this app to manage their health. These results form the basis for further development so that SatuSehat continues to innovate and benefit the health of generation Z as the main users in the future.
Keywords
Article Keywords
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-BY 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
License: All articles are licensed under 
Bening, M., Wibowo, K. A., & Fuady, I. (2021). Aplikasi Mhealth Covid-19 Di Indonesia: Analisis Konten Menggunakan Mobile Aplication Rating Scale (Mars). SINTECH (Science and Information Technology) Journal, 4(2), 163-172. DOI: https://doi.org/10.31598/sintechjournal.v4i2.889.
Putri, L. E. D., & Prabowo, F. S. A. (2015). Pengaruh Electronic Word of Mouth (E-WOM) Terhadap Purchase Intention (Studi kasus pada Go-Jek Indonesia). eProceedings of Management, 2(3).
Sunjaya, A. P. (2019). Potensi, Aplikasi dan Perkembangan Digital Health di Indonesia. Journal Of The Indonesian Medical Association, 69(4), 167-169.
Indrawati, P. D. (2015). Metode Penelitian Manajemen dan Bisnis Konvergensi Teknologi Komunikasi dan Informasi. Bandung: PT Refika Aditama.
Sugiyono, P. D. (2017). Metode penelitian bisnis: pendekatan kuantitatif, kualitatif, kombinasi, dan R&D. Penerbit CV. Alfabeta: Bandung, 225, 87.
Marcolino, M. S., Oliveira, J. A. Q., D'Agostino, M., Ribeiro, A. L., Alkmim, M. B. M., & Novillo-Ortiz, D. (2018). The impact of mHealth interventions: systematic review of systematic reviews. JMIR mHealth and uHealth, 6(1), e8873. https://doi.org/10.2196/mhealth.8873.
Candiwan, C., Sari, P. K., & Sharif, O. O. (2022, July). Information Security Awareness Evaluation of Telemedicine Application Users using Human Aspect Information System Questionnaire. In 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED) (pp. 1-6). IEEE. DOI: 10.1109/ICCED56140.2022.10010445.
Masrury, R. A., & Alamsyah, A. (2019, July). Analyzing tourism mobile applications perceived quality using sentiment analysis and topic modeling. In 2019 7th international conference on information and communication technology (ICoICT) (pp. 1-6). IEEE. DOI: 10.1109/ICoICT.2019.8835255.
Alamsyah, A., & Fadila, T. (2021, July). Increased accuracy of prediction hepatitis disease using the application of principal component analysis on a support vector machine. In Journal of Physics: Conference Series (Vol. 1968, No. 1, p. 012016). IOP Publishing.