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Abstract

Technological developments have accelerated the advancement of assistive technology, hence increasing human life feasibility. One of which is smart wheelchairs with a voice recognition to facilitate people with disability. However, from various smart wheelchair developments, there have been no detailed test results related to the efficiency analysis, the feasibility of the voice recognition feature on the smart wheelchair, and the satisfaction of users in using it. In this study, observations were conducted using a simple regression method, and test user satisfaction using the USE questionnaire. Based on calculation results, the learnability score was 78.81%, indicating that the wheelchair was easy to understand. The efficiency score was 85%, meaning that users found it easy to carry out their daily activities. The memorability score was 85%, indicating that it was easy to remember. The error score was 77.38%, meaning that smart wheelchairs were easy to use. The satisfaction score was 88.57%, meaning that the users felt very comfortable. The conclusion is users are satisfied with smart wheelchairs using voice recognition, meaning that it provides feasible use for a variety of people with disability. The results can be used as a foundation in continuing the development of technological features in smart wheelchairs.

Keywords

People with disabilities Smart wheelchair Voice recognition Simple linear regression USE questionnaire

Article Details

How to Cite
Fathanah Muntasir, N., Muhammad Risafli Raif, Rahmat Hermawan, & Muh. Anshar. (2023). Feasibility Analysis of Smart Wheelchairs Based on Voice Recognition for People with Disability . Enthusiastic : International Journal of Applied Statistics and Data Science, 3(1), 85–96. https://doi.org/10.20885/enthusiastic.vol3.iss1.art8
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References

  1. A.R. Afiyah, “Analisis Speaker Recognition menggunakan Metode Dynamic Time Warping (DTW) Berbasis MATLAB,” Journal of Education, vol. 1, pp. 929–930, 2018.
  2. N. Fita, I. Prayoga, Y. Astuti, and C.B. Waluyo, “Analisis Speaker Recognition menggunakan Metode Dynamic Time Warping (DTW) Berbasis MATLAB,” AVITEC, vol. 1, no. 1, pp. 77–85, 2019, doi: 10.28989/avitec.v1i1.492.
  3. Findbiometrics, http://findbiometrics.com/solutidons/voicespeech-recognition/ (accessed 15 June 2022).
  4. K.A. Imania, S.K. Bariah, “Rancangan Pengembangan Instrumen Penilaian Pembelajaran Berbasis Daring,” Jurnal Teknologi Informasi dan Komunikasi (PETIK), vol. 5, no. 1, pp. 31¬–47, 2019, doi: 10.31980/jpetik.v5i1.445.
  5. R. Prayudha, “Wired and Cordless Wheelchair Movement Control Media for Disabilities,” in Proceeding of the 1st Epi International Conference on Science and Engineering, 2019.
  6. “Law on Disabilities,” Law of the Republic of Indonesia Number 8 of 2016.
  7. S.W.H. Assembly and M. States, “Policy Brief: Access to Assistive Technology,” 5, (2018).
  8. M. Rojas, P. Pedro, M. Arturo, “A Fuzzy Logic Navigation Controller Implemented in Hardware for an Electric Wheelchair,” International Journal of Advanced Robotic Systems, vol. 5, no. 1, 2018, doi: 10.1177/1729881418755.
  9. V.A. Ervanda, D. Syauqy, and F. Utaminingrum, “Pengembangan Sistem Deteksi Gerakan Kepala Sebagai Kontrol Pergerakan Kursi Roda Berbasis Embedded System,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 1, 2018.
  10. S. Klar, and T.J. Leeper, “Identities and Intersectionality: A Case for Purposive Sampling in Survey‐Experimental Research,” in Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment, P. Lavrakas, M. Traugott, C. Kennedy, A. Holbrook, E. de Leeuw, B. West, Eds. NY, USA: John Wiley & Sons, Inc., 2019, ch. 21, pp. 419–433.
  11. E. Sudarmanto et al., Desain Penelitian Bisnis: Pendekatan Kuantitatif. Medan, Indonesia: Yayasan Kita Menulis, 2021.
  12. K. Uswatun, Analisis Regresi. Yogyakarta, Yogyakarta: UAD Press, 2021.
  13. H.T. Saidah, M.A. Gasbara, N.S.A. Lily, E.T. Tosida, M.S.N. Ishlah, “Usability Testing on Android-based KMS for Pregnant Women Using the USE Questionnaire,” International Journal of Quantitative Research and Modeling, vol. 1, no. 3, pp. 164–173, 2020, doi: 10.46336/ijqrm.v1i3.61.
  14. K.R. Hadi, H.M. Az-Zahra, and Lutfi Fanani, “Analisis dan Perbaikan Usability Aplikasi Mobile KAI Access Dengan Metode Usability Testing dan Use Questionnaire,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 9, pp. 2742–2750, 2018.
  15. A. Sasongko, W.E. Jayanti, and D. Risdiansyah, “USE Questionnaire Untuk Mengukur Daya Guna Sistem Informasi e-Tadkzirah,” Jurnal Khatulistiwa Informatika (JKI), vol. 8, no. 2, pp. 80–87, 2020, doi: 10.31294/jki.v8i2.9135.