Lauzzadani, Rayhan (2026) Pengembangan Aplikasi Healthcare Intelligence System untuk Pemantauan Kesehatan Ibu dan Anak: Modernisasi Aplikasi dengan Fitur Rekomendasi MPASI Balita. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Aplikasi Healthcare Intelligence System “SiBunda” mendukung pemantauan kesehatan ibu dan anak melalui pencatatan data, visualisasi pertumbuhan, dan sistem peringatan dini. Namun, versi sebelumnya belum menyediakan rekomendasi gizi balita serta masih menggunakan arsitektur monolithic berbasis Laravel–PostgreSQL dan basis kode Flutter versi lama. Tugas akhir ini memodernisasi SiBunda melalui migrasi backend ke arsitektur serverless berbasis Firebase, modernisasi aplikasi Flutter menggunakan pendekatan feature-first yang mengacu pada prinsip Clean Architecture, serta integrasi layanan Machine Learning untuk menghasilkan rekomendasi gizi balita. Aplikasi diuji melalui pengujian fungsional, reliability, scalability, kompatibilitas, dan usability. Hasil pengujian menunjukkan bahwa fungsi utama aplikasi berjalan dengan baik dan konsisten, sedangkan backend mampu memproses permintaan dari beberapa pengguna virtual secara bersamaan pada lingkungan pengujian lokal. Aplikasi juga dapat berjalan dengan baik pada konfigurasi Android yang diuji. Pengujian usability terhadap 10 responden menghasilkan rata-rata skor SUS sebesar 80,25, yang berada di atas nilai pembanding 68. Hasil tersebut menunjukkan bahwa modernisasi backend dan aplikasi Flutter berhasil dilakukan, layanan rekomendasi gizi berhasil diintegrasikan, dan aplikasi dapat diterima dari aspek kemudahan penggunaan.
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The Healthcare Intelligence System application “SiBunda” supports maternal and child health monitoring through data recording, growth visualization, and an early warning system. However, the previous version did not provide nutritional recommendations for children under five and still relied on a monolithic Laravel–PostgreSQL architecture and a legacy Flutter codebase. This final project modernizes SiBunda by migrating the backend to a Firebase-based serverless architecture, modernizing the Flutter application using a feature-first approach guided by Clean Architecture principles, and integrating a Machine Learning service to generate nutritional recommendations for children under five. The application was evaluated through functional, reliability, scalability, compatibility, and usability testing. The results showed that the main application functions operated successfully and consistently, while the backend was able to process concurrent requests from multiple virtual users in a local testing environment. The application also functioned properly across the tested Android configurations. Usability testing involving 10 respondents resulted in an average SUS score of 80.25, which was above the benchmark score of 68. These results indicate that the backend and Flutter application were successfully modernized, the nutritional recommendation service was successfully integrated, and the application was acceptable in terms of ease of use.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Healthcare Intelligence System, kesehatan ibu dan anak, rekomendasi gizi balita, Flutter, Firebase, Clean Architecture, Machine Learning, Healthcare Intelligence System, maternal and child health, nutritional recommendations for children under five, Flutter, Firebase, Clean Architecture, Machine Learning. |
| Subjects: | Q Science > QA Mathematics > QA76.758 Software engineering Q Science > QA Mathematics > QA76.9.I58 Recommender systems (Information filtering) T Technology > T Technology (General) > T58.6 Management information systems |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis |
| Depositing User: | Rayhan Lauzzadani |
| Date Deposited: | 29 Jul 2026 01:30 |
| Last Modified: | 29 Jul 2026 01:30 |
| URI: | http://repository.its.ac.id/id/eprint/139198 |
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