Evaluasi Usabilitas dan Kinerja Pelaporan Aplikasi BOS V2 Bhabinkamtibmas: Kerangka Analitik SUS–Regresi dengan Rancangan Ekstensi Machine Learning

Leo Nisya Sagita; Lucia Nugraheni Harnaningrum

doi:10.56427/jcbd.v5i3.1034

Authors

Leo Nisya Sagita Universitas Teknologi Digital Indonesia
Lucia Nugraheni Harnaningrum Universitas Teknologi Digital Indonesia

DOI:

https://doi.org/10.56427/jcbd.v5i3.1034

Keywords:

System Usability Scale, Usabilitas, Kinerja Pelaporan, Regresi Linear Berganda, Aplikasi Pelaporan Kepolisian

Abstract

Aplikasi mobile pelaporan internal Bhabinkamtibmas, seperti Binmas Online System versi 2 (BOS V2), menempati posisi strategis dalam infrastruktur pelaporan Polri, namun evaluasi usabilitasnya yang mengaitkan instrumen baku dengan kinerja pelaporan masih jarang didokumentasikan. Penelitian ini mengevaluasi usabilitas BOS V2 dan hubungannya dengan kinerja pelaporan melalui kerangka analitik kuantitatif yang menggabungkan System Usability Scale (SUS) versi Indonesia, korelasi Spearman, dan regresi linear berganda, dengan modul machine learning (K-Means, Random Forest, IndoBERT, dan BERTopic) diformalisasi sebagai ekstensi untuk studi lanjutan. Data diperoleh dari pilot survei terhadap 50 personel Bhabinkamtibmas pada lima Polres di wilayah Polda DIY. Skor SUS rata-rata 55,95 (SD = 14,92) menempatkan BOS V2 pada kategori marginal, dengan reliabilitas Cronbach's α = 0,761. Korelasi Spearman antara SUS dan kinerja pelaporan agregat kuat dan signifikan (ρ = 0,732; p < 0,001), sementara regresi berganda (n = 45) menghasilkan R² = 0,679 dengan SUS sebagai prediktor signifikan (β = 0,0371; p < 0,001). Diagnostik model menunjukkan asumsi klasik terpenuhi (VIF < 1,5; Breusch–Pagan p = 0,849; Shapiro–Wilk p = 0,191). Temuan menunjukkan penyederhanaan alur pengisian sebagai prioritas perbaikan, dan pipeline analitik siap diaktifkan pada studi validasi berskala penuh setelah izin institusional dan persetujuan etik diperoleh.

Downloads

Download data is not yet available.

References

[1] P. Weichbroth, “Usability Testing of Mobile Applications: A Methodological Framework,” Applied Sciences (Switzerland), vol. 14, no. 5, Mar. 2024, doi: 10.3390/app14051792.

[2] A. M. Deshmukh and R. Chalmeta, “Validation of system usability scale as a usability metric to evaluate voice user interfaces,” PeerJ Comput. Sci., vol. 10, p. e1918, 2024, doi: 10.7717/peerj-cs.1918.

[3] J. R. Lewis, "The System Usability Scale: Past, present, and future," Int. J. Hum.-Comput. Interact., vol. 34, no. 7, pp. 577–590, 2018, doi: 10.1080/10447318.2018.1455307

[4] J. Sauro and J. R. Lewis, "Standardized usability questionnaires," in Quantifying the User Experience: Practical Statistics for User Research, 2nd ed. Cambridge, MA: Morgan Kaufmann, 2016, ch. 8, pp. 185–248, doi: 10.1016/B978-0-12-802308-2.00008-4

[5] A. Ghorayeb, J. L. Darbyshire, M. W. Wronikowska, and P. J. Watkinson, “Design and validation of a new Healthcare Systems Usability Scale (HSUS) for clinical decision support systems: a mixed-methods approach,” BMJ Open, vol. 13, no. 1, Jan. 2023, doi: 10.1136/bmjopen-2022-065323.

[6] Z. Sharfina and H. B. Santoso, “An Indonesian adaptation of the System Usability Scale (SUS),” in 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS), Malang, Indonesia: IEEE, Oct. 2016, pp. 145–148. doi: 10.1109/ICACSIS.2016.7872776.

[7] B. Rahimi, H. Nadri, H. L. Afshar, and T. Timpka, “A systematic review of the technology acceptance model in health informatics,” Jul. 01, 2018, Georg Thieme Verlag. doi: 10.1055/s-0038-1668091.

[8] L. Xue, A. M. Rashid, and S. Ouyang, “The Unified Theory of Acceptance and Use of Technology (UTAUT) in Higher Education: A Systematic Review,” Jan. 01, 2024, SAGE Publications Inc. doi: 10.1177/21582440241229570.

[9] C. F. Finch, N. Goode, L. Shaw, and P. M. Salmon, “End-user experiences with two incident and injury reporting systems designed for led outdoor activities - Challenges for implementation of future data systems,” Inj. Epidemiol., vol. 6, no. 1, Sep. 2019, doi: 10.1186/s40621-019-0214-y.

[10] P. Kureerung, L. Ramingwong, S. Ramingwong, K. Cosh, and N. Eiamkanitchat, “A Framework for Designing Usability: Usability Redesign of a Mobile Government Application,” Information (Switzerland), vol. 13, no. 10, Oct. 2022, doi: 10.3390/info13100470.

[11] Alifia Maharani, “Usability Analysis on E-Letter Website FST UIN Syarif Hidatullah Jakarta Using SUS Questionnaire Method,” Journal of Computers and Digital Business, vol. 3, no. 1, pp. 36–42, Jan. 2024, doi: 10.56427/jcbd.v3i1.43.

[12] M. Afif, “Examining the usability of mobile applications among undergraduate students using SUS and data mining techniques,” International Journal of Data and Network Science, vol. 8, no. 3, pp. 1801–1814, Jun. 2024, doi: 10.5267/j.ijdns.2024.2.008.

[13] A. K. Jain, “Data clustering: 50 years beyond K-means,” Pattern Recognit. Lett., vol. 31, no. 8, pp. 651–666, Jun. 2010, doi: 10.1016/j.patrec.2009.09.011.

[14] L. Breiman, “Random Forests,” Mach. Learn., vol. 45, no. 1, pp. 5–32, Oct. 2001, doi: 10.1023/A:1010933404324.

[15] G. Ranjbaran, D. R. Recupero, C. K. Roy, and K. A. Schneider, “C-SHAP: A Hybrid Method for Fast and Efficient Interpretability,” Applied Sciences, vol. 15, no. 2, pp. 1–23, Jan. 2025, doi: 10.3390/app15020672.

[16] B. Wilie et al., “IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding,” in Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, K.-F. Wong, K. Knight, and H. Wu, Eds., Suzhou, China: Association for Computational Linguistics, Dec. 2020, pp. 843–857. doi: 10.18653/v1/2020.aacl-main.85.

[17] R. Egger and J. Yu, “A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts,” Frontiers in Sociology, vol. Volume 7-2022, 2022, doi: 10.3389/fsoc.2022.886498.