Evaluasi Usability Aplikasi Lazarillo pada Pengguna Low Vision dengan Pendekatan Kombinasi Usability Testing, UEQ+ dan Semi Structured Interview

Abstract

Audio-based navigation applications like Lazarillo are developed to enhance the mobility and independence of users with blindess. Although it offers voice-guided navigation features in multiple languages including Indonesian, the application's effectiveness for users with low vision still requires deeper evaluation. This study employed a combination of usability testing, User Experience Questionnaire+ (UEQ+), and semi-structured interviews to thoroughly evaluate Lazarillo.

Pedestrian navigation tasks were conducted to measure the application's effectiveness and efficiency. UEQ+ was utilized to assess the users’ subjective experience, while semi-structured interviews explored additional issues not captured through questionnaires. Usability testing results showed an effectiveness score of 60%, categorized as moderately effective, and an efficiency score of 93.46%, indicating almost excellent task completion time. In the UEQ+ results, the highest score was obtained in the perspicuity scale, while the lowest scores appeared in the efficiency and response behavior dimensions, highlighting areas for improvement.

Findings from the semi-structured interviews revealed problems such as delayed navigation notifications, inaccuracies in nearby location information, and inconsistencies in language between Indonesian and English within the app. Based on these findings, improvement recommendations focused on optimizing real-time navigation systems, adjusting the exploration feature to minimize user distraction, and ensuring consistent use of the local language throughout the application.

The conclusion of this study shows that Lazarillo demonstrates enough performance in terms of efficiency and effectiveness but still requires improvements in navigation accuration and system response behavior. The combination of methods successfully revealed key weaknesses and provided usability-based recommendations to enhance the experience for low vision users.