Febriana, Nur Baity (2026) Pengembangan Timbangan Bayi Digital Berbasis Fuzzy Decision Support System yang Terintegrasi IoT untuk Pemantauan Tumbuh Kembang Bayi pada Tahun Pertama. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pemantauan pertumbuhan dan perkembangan bayi pada 1.000 hari pertama kehidupan merupakan aspek penting dalam pencegahan stunting, yang masih menjadi salah satu permasalahan kesehatan di Indonesia dengan prevalensi mencapai 19.8% pada tahun 2024. Pelaksanaan pengukuran antropometri di Posyandu umumnya masih dilakukan secara manual sehingga berpotensi menimbulkan kesalahan pencatatan, ketidaksesuaian interpretasi, serta belum terintegrasi secara otomatis dengan standar pertumbuhan WHO. Penelitian ini bertujuan mengembangkan timbangan bayi digital berbasis Internet of Things (IoT) dan Fuzzy Decision Support System (FDSS) untuk memproses pengukuran dan klasifikasi status gizi bayi usia 0–12 bulan. Sistem yang dikembangkan mampu mengukur tiga parameter antropometri secara simultan, yaitu berat badan menggunakan sensor load cell dengan penguat ADS1232, panjang badan menggunakan rotary encoder Omron, serta lingkar kepala menggunakan metode image processing berbasis Raspberry Pi dan kamera. Data hasil pengukuran diproses menggunakan FDSS berdasarkan Z-score WHO yang disesuaikan dengan usia dan jenis kelamin bayi, kemudian dikirim secara nirkabel ke basis data. Pengujian dilakukan terhadap 42 bayi dari empat Posyandu di Kota Surabaya dengan total 115 sesi pengukuran. Hasil pengujian menunjukkan rata-rata error sebesar 1.37% untuk berat badan, 4.54% untuk panjang badan, dan 2.48% untuk lingkar kepala. Sistem berhasil melakukan klasifikasi status gizi secara otomatis sesuai standar WHO serta mendukung pengelolaan data pertumbuhan bayi pada berbagai Posyandu.
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Monitoring infant growth and development during the first 1.000 days of life is a critical aspect of stunting prevention, which remains one of Indonesia's major health issues, with a prevalence reaching 19.8% in 2024. Anthropometric measurements at Posyandu are generally still performed manually, which may lead to recording errors, inconsistent interpretation, and a lack of automatic integration with WHO growth standards. This study aims to develop a digital infant weighing device based on the Internet of Things (IoT) and a Fuzzy Decision Support System (FDSS) to process measurements and classify the nutritional status of infants aged 0–12 months. The developed system is capable of simultaneously measuring three anthropometric parameters: body weight using a load cell sensor with an ADS1232 amplifier, body length using an Omron rotary encoder, and head circumference using an image processing method based on a Raspberry Pi and camera. The measurement data are processed using the FDSS based on WHO Z-scores adjusted for the infant's age and sex, then wirelessly transmitted to a database. Testing was conducted on 42 infants from four Posyandu in the city of Surabaya, with a total of 115 measurement sessions. The results showed an average error of 1.37% for body weight, 4.54% for body length, and 2.48% for head circumference. The system successfully performed automatic nutritional status classification in accordance with WHO standards and supports the management of infant growth data across multiple Posyandu.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Stunting, Internet of Things (IoT), Fuzzy Decision Support System (FDSS), Antropometri Bayi, Posyandu Stunting, Internet of Things (IoT), Fuzzy Decision Support System (FDSS), Infant Anthropometry, Posyandu. |
| Subjects: | T Technology > T Technology (General) > T57.74 Linear programming T Technology > T Technology (General) > T58.62 Decision support systems T Technology > T Technology (General) > T59.7 Human-machine systems. T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques. Image analysis--Data processing. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis |
| Depositing User: | Febriana Nur Baity |
| Date Deposited: | 02 Aug 2026 18:50 |
| Last Modified: | 02 Aug 2026 18:52 |
| URI: | http://repository.its.ac.id/id/eprint/140622 |
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