학술논문

Increasing Visual Display Quality Using Usability Test for Adaptive Queue Line System: Case study at Jakarta MRT
Document Type
Conference
Source
대한인간공학회 학술대회논문집. 2021-11 2021(11):94-99
Subject
AQLS
usability test
MRT
visual display
ergonomics
user interface (UI)
Language
Korean
Abstract
Objective: The aim of this study is to improve ease of use the information of Adaptive Queue Line System (AQLS) prototype by using usability test. Background: Visual display is a part of Ergonomics to ensure users friendly of prototype so that the information is more efficiency to understand and reducing error probability. Many factors of user interface (UI) should be considered to evaluate easy to understand and operate the AQLS. The AQLS is a tool to manage the passenger queue line of MRT in increasing its queue discipline alongside its safety. Methods: An initial survey of 30 samples MRT passengers (17 women and 13 men) was conducted to find out what information in AQLS is needed when queuing on the MRT platform. The basic principles of user interfaces, visual display and controls, layout, typography, and Web Content Accessibility Guidelines (WCAG) used to construct AQLS screen. Usability test involved the parameters of learning ability, efficiency, error, and satisfaction were used to improve the quality of the prototype. The number of respondents for the test was 30 people with the composition of 12 men and 18 women. Results: The initial AQLS usability test prototype gave a learnability score with successive rate = 75%, time-based efficiency = 0.108, error rate = 0.233, and satisfaction with SUS (System Usability Scale) on average = 69,667 or categorized as close to good. After making changes, there is an increase in the quality of the prototype with a new SUS value of 82,333 (excellent). Conclusion: Usability tests can be employed to significantly improve the quality and ease of use of the MRT information board by taking into account the weaknesses that must be improved. Application: The AQLS prototype with a SUS value of 82,333 can confidently be implemented at MRT stations to improve crowd management capabilities.

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