Ariyani, Dhina Safira (2025) Sistem Timbangan Bayi Digital Berbasis Fuzzy Decision Support System Dan Pengolahan Citra Kepala untuk Optimalisasi Pengukuran Tumbuh Kembang Anak. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Usia 1000 hari pertama kehidupan merupakan aspek penting penentu tumbuh kembang seseorang. Sementara data menunjukkan prevalensi stunting masih di 21.3% yang masih jauh dari target sebesar 14%. Oleh karena itu, diperlukan pemantauan pengukuran data antropometri anak, yang meliputi berat badan, panjang badan, dan lingkar kepala. Penelitian ini dirancang untuk mengkombinasikan pengukuran berat badan menggunakan sensor loadcell yang dihubungkan dengan modul ADS1232 sebagai rangkaian analog-digital converter, panjang badan menggunakan rotary encoder, dan lingkar kepala menggunakan sensor rotary encoder tambahan. Proses komputasi data menggunakan Arduino MKR WiFi 1010 lanjut menggunakan Single Board Computer (SBC) untuk mendapatkan klasifikasi indeks massa tubuh menurut umur (IMT/U), berat badan menurut umur (BB/U), panjang badan menurut umur (PB/U), dan lingkar kepala menurut umur (LK/U). Metode pengolahan yang digunakan berbasis pada Fuzzy Decision Support System (FDSS) yang berfokus pada anak dengan rentang usia 0 sampai 12 bulan. Hasil penelitian menunjukkan bahwa timbangan yang dirancang telah mampu mengukur parameter antropometri dengan tingkat kesalahan (error) 0.45% pada pengukuran berat badan, 0.48% pada pengukuran panjang badan, dan 1.46% pada pengukuran lingkar kepala. Dari 23 subjek yang berpartisipasi, didapatkan hasil untuk BB/U: 20 subjek normal; PB/U: 16 subjek normal; IMT/U: 19 subjek normal; serta LK/U: 21 subjek normal. Sistem fuzzy layer 2 menghasilkan klasifikasi akhir 18 subjek normal dan 5 subjek abnormal. Keluaran dari hasil klasifikasi menunjukkan kesesuaian dengan standar antropometri WHO Child Growth Standards dan membuktikan bahwa metode FDSS dapat digunakan untuk klasifikasi kondisi komprehensif pada bayi. Pengembangan selanjutnya dari penelitian ini meliputi optimalisasi algoritma fuzzy logic dengan integrasi machine learning, pengembangan sistem komunikasi wireless untuk integrasi dengan sistem informasi kesehatan, serta implementasi aplikasi mobile terintegrasi untuk monitoring pertumbuhan real-time.
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The first 1,000 days of life represent a critical period that determines an individual's growth and development. Meanwhile, data shows that the prevalence of stunting remains at 21.3%, which is still far from the target of 14%. Therefore, monitoring a child's anthropometric measurements—including weight, body length, and head circumference—is essential. This study was designed to integrate weight measurement using a load cell sensor connected to an ADS1232 analog-to-digital converter module, body length measurement using a rotary encoder, and head circumference measurement using a camera that connected with Raspberry Pi. Data processing is carried out using the Arduino MKR WiFi 1010 and a Single Board Computer (SBC) to classify Body Mass Index-for-Age (BMI/A), Weight-for-Age (W/A), Length-for-Age (L/A), and Head Circumference-for-Age (HC/A). The processing method is based on a Fuzzy Decision Support System (FDSS), focusing on children aged 0 to 12 months. The results of the study show that the designed scale system was able to measure anthropometric parameters with an error rate of 0.45% for weight, 0.48% for body length, and 1.46% for head circumference. Among the 23 subjects who participated, the classification results were as follows: W/A – 20 subjects categorized as normal; L/A – 16 subjects normal; BMI/A – 19 subjects normal; and HC/A – 21 subjects normal. The second-layer fuzzy system produced a final classification of 18 subjects as normal and 5 as abnormal. The classification outcomes are consistent with the WHO Child Growth Standards and demonstrate that the FDSS method can be used to classify the comprehensive health condition of infants. Future development of this research includes the optimization of the fuzzy logic algorithm through integration with machine learning, the development of wireless communication systems for integration with health information systems, and the implementation of an integrated mobile application for real-time growth monitoring.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Sistem Timbangan Bayi Digital, Fuzzy Decision Support System, Tumbuh Kembang Bayi, Head Image Processing, Digital Baby Scale System, Fuzzy Decision Support System, Baby Growth and Development, Head Image Processing |
| 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: | Safira Dhina Ariyani |
| Date Deposited: | 05 Aug 2025 06:52 |
| Last Modified: | 05 Aug 2025 06:52 |
| URI: | http://repository.its.ac.id/id/eprint/126772 |
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