Elektronik/Digital

Visual Cohort Baby Recording Based on Internet of Things for Maternal and Child Health Service

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Maternal and Child Health Service is a health service that makes it easier for the public to monitor the growth and development of infants and toddlers. The people who get this health
service are infants less than one year old and toddlers aged 1 to 5 years. Maternal and Child Health Service in the community, especially in rural areas, the medical equipment used is still inadequate, for example to weigh infants and toddlers, maternal and child health official use scales commonly used to weigh rice. Periodically babies and toddlers are weighed by medical personnel, and the results are then recorded in the maternal and child book. In some cases, the registration process is still not efficient, because the possibility of the book being lost. The aim of this research is to design and develop a Posyandu Information System Application as an early warning system for Maternal and Child Health. In this research, first coding from four sensors used are heart rate sensor, weight sensor, temperature sensor and ultrasonic sensor. In the microcontroller, the Artificial Neural Network artificial intelligence method is embedded to learn from inputs to classify decisions / action information from the sensor medical record results. Medical record data and learning outcomes from Artificial Neural Network (ANN) Algorithm will be sent using Internet of Things modules on the server so that they can be accessed by the application server both web and mobile. Visualization of medical record data and the results of the health conditions of infants and toddlers recapitulated on the cohort book periodically and form of cohort graphical report. With the early warning system in the form of a Posyandu Information System Application it is expected that pregnant women or toddlers who have health problems can immediately obtain information as early as possible.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

Sidoarjo : Universitas Muhammadiyah Sidoarjo., 2023

Deskripsi Fisik

13 hlm.

Bahasa

Inggris

ISBN/ISSN

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Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Internet of Things
Artificial Neural Network (ANN)

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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