PENDETEKSI DAN ALARM PASIEN STROKE SAAT JATUH DENGAN SENSOR GY-85 SECARA IOT

LASAKAR, ARYO GERBANG SAMUDRA (2019) PENDETEKSI DAN ALARM PASIEN STROKE SAAT JATUH DENGAN SENSOR GY-85 SECARA IOT. S1 thesis, Universitas Mercu Buana.

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Abstract

Stroke is one of the most dangerous diseases and can cause death with patients who are not a few involved. This disease can affect anyone and with a fairly wide age range. In 2018 the disease of determining the position of the disease caused the number two death in Indonesia. More than 70 percent of people post-stroke are at home and three-quarters of those who fall cannot rise afterwards. Of those who fell, 10 percent managed to get injured, recover, and fracture, and could be released if they were not immediately helped. The researcher conducted a literature study, designing, procuring components, analysis, and testing the system with the aim of creating a stroke detection and alarm device when completed by IoT. The researcher decided to use NodeMCU and GY-85 sensors as the main components, Arduino IDE as a programming system software, and Blynk as an IoT platform. This study discusses the value read by the sensor when the patient falls, the patient's fall position, the speed of data and email delivery with IoT. The results of this study are that the research gets a sensor value that can be used to find out when the current falls and its position, the data delivery speed is 0,5 seconds, and the email delivery speed is 5 seconds. Keywords: Arduino IDE, GY-85, Detection System and Alarm, NodeMCU, Stroke, Fall, IoT. Stroke merupakan salah satu penyakit yang paling berbahaya dan dapat menyebabkan kematian dengan penderita yang tidak sedikit pula jumlahnya. Penyakit ini dapat menyerang siapa saja dan dengan rentang usia yang cukup luas. Pada tahun 2018 stroke menempati posisi penyakit penyebab kematian nomer dua di Indonesia. Lebih dari 70 persen orang pasca stroke yang jatuh berada di rumah dan tiga-perempat dari mereka yang jatuh tidak mampu bangkit sesudahnya. Dari mereka yang jatuh, 10 persen mengalami cedera serius, hilangnya kesadaran, dan patah tulang, dan dapat mengakibatkan kematian bila tidak segera ditolong. Peneliti melakukan studi literatur, perancangan, pengadaan komponen, analisa, dan pengujian sistemdengan tujuan menciptakan alat pendeteksi dan alarm pasien stroke saat jatuh secara IoT. Peneliti memutuskan menggunakan NodeMCU dan sensor GY-85 sebagai komponen utama, Arduino IDE sebagai software pemrograman sistem, dan Blynk sebagai platform IoT. Penelitian ini bertujuan untuk mengetahui nilai yang terbaca oleh sensor pada saat pasien jatuh, posisi jatuh pasien, kecepatan pengiriman data dan email secara IoT. Hasil penelitian ini adalah peneliti mendapatkan nilai sensor yang dapat digunakan untuk mengetahui saat pasen jatuh dan posisinya, kecepatan pengiriman data 0,5 detik, dan kecepatan pengiriman email 5 detik. Kata Kunci: Arduino IDE, GY-85, Sistem Pendeteksi dan Alarm, Node MCU, Stroke, Jatuh, IoT.

Item Type: Thesis (S1)
Call Number CD: FT/ELK. 19 008
Call Number: ST/14/19/048
NIM/NIDN Creators: 41417110056
Uncontrolled Keywords: Arduino IDE, GY-85, Sistem Pendeteksi dan Alarm, Node MCU, Stroke, Jatuh, IoT.
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem > 003.1 System Identification/Identifikasi Sistem
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem > 003.7 Kinds of Systems/Macam-macam Sistem
Divisions: Fakultas Teknik > Teknik Elektro
Depositing User: Dede Muksin Lubis
Date Deposited: 13 Jan 2022 11:18
Last Modified: 19 Oct 2022 02:45
URI: http://repository.mercubuana.ac.id/id/eprint/54243

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