Enhancement of The User Interface Features of The Digital Population Identity Application Using Machine Learning and Design Thinking Methods

Authors

  • Tassya Adelia Putri Institut Teknologi Sepuluh Nopember
  • Bagus Jati Santoso Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.59141/jrssem.v5i7.1337

Keywords:

Digital Population Identity (IKD), Machine Learning, Naïve Bayes, Design Thinking, Password

Abstract

Abstract. As an implementation of the One Agency One Innovation policy issued by the Ministry of PANRB, the Population and Civil Registration Office launched the Identitas Kependudukan Digital (IKD) application. IKD is an electronic ID card in digital form that contains population data and documents within a mobile application accessible via a smartphone. It displays the owner's personal information as a valid official identity, allowing it to be used across various population administration services digitally. However, the application faces several challenges, including low adoption rates, poor user ratings (3.2 on the Google Play Store), and technical constraints. This study aims to introduce additional features to the IKD (Digital Population Identity) application to enhance usability, interaction efficiency, and the overall user experience (UI/UX). This research employs both quantitative and qualitative methods through the integration of machine learning and design thinking. The empathize stage utilized sentiment analysis using the Naive Bayes algorithm on 9,906 user reviews from the Google Play Store, along with a baseline questionnaire of 271 respondents. Machine learning analysis, achieving 94.1% accuracy, identified dominant negative sentiments related to login failures, complex face-to-face verification, and the absence of password or PIN reset features. Based on these findings, the design thinking process produced a solution design featuring Single Sign-On functionality, password or PIN reset options, FAQs, and online queuing services. Validation testing of the new design showed a significant improvement, with an average score of 4.49 out of 5, indicating very positive user acceptance.

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Published

2026-02-21

How to Cite

Adelia Putri, T., & Jati Santoso, B. (2026). Enhancement of The User Interface Features of The Digital Population Identity Application Using Machine Learning and Design Thinking Methods. Journal Research of Social Science, Economics, and Management, 5(7), 10290–10298. https://doi.org/10.59141/jrssem.v5i7.1337

Issue

Vol. 5 No. 7 (2026): Journal Research of Social Science, Economics, and Management

Section

Articles

License

Copyright (c) 2026 Tassya Adelia Putri, Bagus Jati Santoso

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