Peningkatan Fitur Antarmuka Aplikasi Identitas Kependudukan Digital (IKD) Menggunakan Metode Machine Learning Dan Design Thinking

Putri, Tassya Adelia (2026) Peningkatan Fitur Antarmuka Aplikasi Identitas Kependudukan Digital (IKD) Menggunakan Metode Machine Learning Dan Design Thinking. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sebagai implementasi kebijakan One Agency One Innovation yang dikeluarkan oleh Kementerian PANRB, Dinas Kependudukan dan Pencatatan Sipil meluncurkan aplikasi Identitas Kependudukan Digital (IKD). IKD merupakan KTP elektronik dalam bentuk digital yang memuat data dan dokumen kependudukan dalam aplikasi digital melalui gawai (smartphone) dengan menampilkan informasi pribadi pemilik sebagai identitas resmi yang sah, sehingga dapat digunakan dalam berbagai layanan administrasi kependudukan secara digital. Namun, aplikasi ini menghadapi tantangan rendahnya adopsi, rating pengguna yang buruk yaitu 3,2 pada Google Play Store, dan kendala teknis. Penelitian ini bertujuan untuk merancang ulang antarmuka aplikasi IKD guna meningkatkan pengalaman pengguna (User Experience/User Interface). Penelitian ini menggunakan metode kuantitatif dan kualitatif dengan integrasi machine learning dan design thinking. Tahap empathize menggunakan analisis sentimen algoritma Naive Bayes terhadap 9.906 ulasan pengguna di Google Play Store dan kuesioner baseline terhadap 271 responden. Analisis machine learning dengan akurasi 94,1% mengidentifikasi dominasi sentimen negatif terkait kegagalan login, verifikasi tatap muka yang mempersulit, dan ketiadaan fitur reset password atau pin. Berdasarkan temuan tersebut, proses design thinking menghasilkan desain solusi berupa fitur Single Sign-On, reset PIN atau password, FAQ dan layanan antrean online. Pengujian validasi desain baru menunjukkan peningkatan signifikan dengan skor rata-rata 4,49 dari skala 5, yang mengindikasikan penerimaan pengguna yang sangat positif. Integrasi machine learning dan design thinking terbukti efektif dalam memetakan permasalahan krusial dan menghasilkan solusi desain antarmuka yang mampu meningkatkan usability serta kepuasan pengguna aplikasi IKD secara konkret.
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As an implementation of the One Agency One Innovation policy issued by the Ministry of Administrative and Bureaucratic Reform (PANRB), the Population and Civil Registration Agency (Dinas Kependudukan dan Pencatatan Sipil) launched the Identitas Kependudukan Digital or IKD application. IKD serves as a digital form of the electronic ID card that contains population data and documents accessible via smartphones, displaying personal information as a valid official identity to facilitate various digital population administration services. However, this application faces challenges such as low adoption, poor user ratings (3.2 on Google Play Store), and technical constraints. This study aims to redesign the IKD application interface to enhance User Experience and User Interface. This research employs mixed methods (quantitative and qualitative) by integrating 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 and a baseline questionnaire administered to 271 respondents. machine learning analysis, with an accuracy of 94.1%, identified a dominance of negative sentiments regarding login failures, cumbersome face-to-face verification, and the absence of password or PIN reset features. Based on these findings, the design thinking process produced solution designs featuring Single Sign-On, PIN or password reset capabilities, FAQs, and online queuing services. Validation testing of the new design demonstrated a significant improvement with an average score of 4.49 out of 5, indicating very positive user acceptance. The integration of machine learning and design thinking proved effective in mapping crucial issues and generating interface design solutions that concretely improve the usability and user satisfaction of the IKD application.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Identitas Kependudukan Digital (IKD), Machine Learning, Design Thinking, Password, PIN, FAQ, Antrean, Google Playstore, Queue.
Subjects:	Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines. T Technology > T Technology (General) > T56.8 Project Management
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT)
Depositing User:	Tassya Adelia Putri
Date Deposited:	26 Jan 2026 05:03
Last Modified:	26 Jan 2026 05:03
URI:	http://repository.its.ac.id/id/eprint/130303

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