Instrumentasi Timbangan Bayi Portable Berbasis Fuzzy Decision Support System untuk Deteksi Dini Stunting pada Bayi

Lestarini, Ni Luh Ayu Lista (2023) Instrumentasi Timbangan Bayi Portable Berbasis Fuzzy Decision Support System untuk Deteksi Dini Stunting pada Bayi. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Stunting merupakan gangguan pertumbuhan dan perkembangan anak yang disebabkan oleh efek kumulatif dari kekurangan gizi dan infeksi berulang, baik sebelum atau sesudah lahir. Sehingga dalam proses diagnosis dapat dilakukan melalui pengambilan data antropometri untuk menilai status gizi anak. Kondisi stunting menunjukan malnutrisi kronis yang berdampak terhadap gangguan perkembangan fisik dan kognitif apabila tidak ditangani dengan baik. Namun banyak orangtua yang kurang menyadari hingga anak sudah mengalami kondisi stunting tingkat lanjut sehingga sering terjadi keterlambatan tindakan. Oleh karena ini, pada penelitian ini dirancang instrumentasi yang mengkombinasikan antara timbangan bayi digital dan meteran digital dengan sebuah sistem deteksi menggunakan prinsip decision support system yang bertujuan untuk mendeteksi stunting pada bayi. Penelitian ini menggunakan dua jenis data antropometri, yaitu panjang badan dan berat badan bayi dengan usia 0 sampai 12 bulan. Data panjang badan diukur menggunakan rotary encoder dan data berat badan diukur menggunakan sensor load cell yang dihubungkan dengan modul HX71, dimana data sensor dikomputasikan oleh mikrokontroler ESP32 Devkit V1 dan dikirim ke sebuah database menggunakan konektivitas WiFi. Data yang diperoleh dari timbangan digital akan diolah lebih lanjut pada Personal computer untuk mendapatkan nilai indeks massa tubuh dan menentukan hasil deteksi stunting menggunakan metode Fuzzy Decision Support System (FDSS). Hasil penelitian menunjukkan bahwa timbangan yang dirancang telah mampu mengukur berat badan dan panjang badan, dengan tingkat kesalahan (eror) 0,23% pada pengukuran berat badan dan 0,13% pada pengukuran panjang badan. Selain itu, keluaran dari hasil deteksi menunjukkan kesesuaian dengan standar antropometri yang telah ditetapkan dan membuktikkan bahwa metode FDSS dapat digunakan untuk mendeteksi stunting pada bayi.
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The growth and developmental disease known as stunting affects children and is brought on by chronic malnutrition and recurring infections, either before or after birth. Therefore, the diagnosis process can be conducted through anthropometric data collection to assess the nutritional status of children. Stunting condition indicates chronic malnutrition that impacts physical and cognitive developmental impairments if not properly addressed. However, many parents are not aware of the problem until their child has advanced stunting, which results in delays in taking appropriate measures To address this issue, this research focuses on designing an instrumentation that combines a digital infant scale with a digital meter and a detection system with the goal of identifying stunting in newborns. The length and weight of newborns between the ages of 0 and 12 months are the two forms of anthropometric data used in the study. A rotary encoder is used to measure body length and load cell attached to the HX71 module is used to measure weight. The sensor data is computed by the ESP32 Devkit V1 microcontroller and delivered to a database via Wi-Fi connectivity. The data obtained from the digital scale will be processed on the Personal computer to obtain Body Mass Index (BMI) values and determine the stunting detection using the Fuzzy decision support system (FDSS) method. The designed scales were able to measure body weight and length, with an error rate of 0.23% on weight measurement and 0.13% on body length measurements. Moreover, the output of the detection system shows compliance with established anthropometric standards, validating the effectiveness of the FDSS method in detecting stunting in infants.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Stunting, Antropometri, Load cell, Rotary encoder, Fuzzy logic, Anthropometric
Subjects:	Q Science > QA Mathematics > QA9.64 Fuzzy logic R Medicine > RC Internal medicine > RC78 Diagnosis, Radioscopic--Examinations, questions, etc. T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T58.62 Decision support systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Ni Luh Ayu Lista Lestarini
Date Deposited:	09 Nov 2023 08:06
Last Modified:	09 Nov 2023 08:06
URI:	http://repository.its.ac.id/id/eprint/103389

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