Open AccessRedesign the User Interface of the Purwakarta Disdukcapil Mobile Application Using Kansei Engineering
Author(s) -
Yudhi Raymond Ramadhan,
Imam Ma'ruf Nugroho,
Imam Khaerul Anwar
Publication year - 2022
Publication title -
sinkron
Language(s) - English
Resource type - Journals
eISSN - 2541-2019
pISSN - 2541-044X
DOI - 10.33395/sinkron.v7i1.11240
Subject(s) - kansei engineering , kansei , usability , human–computer interaction , user experience design , user interface , computer science , interface (matter) , cronbach's alpha , multimedia , factor (programming language) , mathematics , parallel computing , operating system , programming language , statistics , bubble , maximum bubble pressure method , descriptive statistics
The function and usability of a mobile application are the main reasons for making the application. In addition, the User Interface (UI) design factor is also an important consideration in making a mobile application. Good UI design is the main attraction for the application to use. There are many ways to make a good UI design. Kansei Engineering (KE) is one of the methods that can be used in the UI design process. Since the creation of the Mobile Disdukcapil application, there has never been a study on the application's design interface. This research aims to make recommendations on design elements desired by users. The KE method can detect the user's feelings towards an interface. So that the KE method will produce a UI design for the Disdukcapil mobile application that is liked by the user. The methodology used refers to the Kansei Engineering Type I methodology. This research uses Kansei Words to represent the emotional factors of the user when viewing a product specimen. Kansei Word used as many as 10 words related to the UI display on the mobile application. The mobile application specimens used were 5 specimens, which were taken from various similar applications. This study involved 80 participants to fill out the questionnaire. The results of the questionnaire were processed using multivariate statistical analysis, namely Cronbach's Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA), and Partial Least Square (PLS). The results of this study are in the form of recommendations for UI design elements based on the most dominant emotional factors. Based on the results of data processing, the dominant emotional factors are "Colorful" and "Simple".