DETERMINATION OF USER EXPERIENCE MEASUREMENT METRICS FOR SPECIFIC DOMAIN USING QUALITATIVE ANALYSIS METHOD

ABSTRACT DETERMINATION OF USER EXPERIENCE MEASUREMENT METRICS FOR SPECIFIC DOMAIN USING QUALITATIVE ANALYSIS METHOD By WILLSEN SENTOSA NIM : 13517036 The rapid advancement of technology with many features has led to the much-needed development of interaction design in applications. However, int...

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Bibliographic Details
Main Author: Sentosa, Willsen
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/64102
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:ABSTRACT DETERMINATION OF USER EXPERIENCE MEASUREMENT METRICS FOR SPECIFIC DOMAIN USING QUALITATIVE ANALYSIS METHOD By WILLSEN SENTOSA NIM : 13517036 The rapid advancement of technology with many features has led to the much-needed development of interaction design in applications. However, interaction design itself is often associated with subjectivity. Because of this, user experience metrics are needed to measure the user experience of an application. However, currently, there are many user experience metrics that are widely distributed and not all of them can measure the user experience of applications on a specific domain with precision. That’s why there is a need of a study for determining the right user experience metrics for specific domains. The domains that are chosen in this study are domains that are currently on the rise during the COVID-19 pandemic, namely Social Media, Music/Podcast Streaming, and Health. To determine right metrics for each domain, an analysis of core features of each domain, determining user experience and usability goals, analysis of metrics that are often used by the public, matching process between domains and metrics, and metrics testing using usability testing to application users. And from the usability testing result, it was found that the metrics that are chosen from matching process are accepted by reliability test and validity test using Pearson Correlation Coefficient, which had a value above 0.6. Keywords: metrics, user experience, usability, domain