This Author published in this journals
All Journal Teknika
Indah Lestari
Information Systems Study Program, Department of Information Technology, Politeknik Caltex Riau, Pekanbaru, Riau, Indonesia

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Manual Clustering Approach for User Group Mapping in Facility Management System UI/UX Design Caylen Marli; Indah Lestari
Teknika Vol. 14 No. 3 (2025): November 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i3.1356

Abstract

The facility management process at Politeknik Caltex Riau is still conducted manually, using paper media and Excel records, which causes inefficiency, delays, and difficulties in monitoring real-time facility availability. To address these problems, a web-based information system was developed with a UI/UX approach using the Design Thinking method. The uniqueness of this study lies in the use of manual clustering as a user segmentation method during the initial stage, performed based on survey results. This technique resulted in three user groups: (1) active borrowers who need tracking and notifications, (2) infrequent borrowers who require clear information, and (3) non-borrowers who focus more on attractive and easy-to-use interface design. These clusters serve as the foundation for creating personas, defining problem statements, and designing key system features. This study was conducted in two cycles. The first cycle involved initial design and testing, while the second cycle involved iterative improvements based on previous evaluation results. Testing using the System Usability Scale (SUS) showed an increase in scores from 75 to 77. Meanwhile, the User Experience Questionnaire (UEQ) exhibited all dimensions in the positive range (>0.8), with the highest score in Stimulation (2.202) and the lowest in Novelty (1.721). These results demonstrate that the manual clustering approach is effective in identifying user needs contextually and supports the design of an efficient, relevant, and user-friendly system.