Fadila, Aka (2024) Prototipe Aplikasi pemantauan postur tubuh berbasis Flex Sensor dengan implementasi algoritma kalman filter. Sarjana thesis, UIN Sunan Gunung Djati Bandung.
|
Text (COVER)
1_cover.pdf Download (406kB) | Preview |
|
|
Text (ABSTRAK)
2_abstrak.pdf Download (127kB) | Preview |
|
|
Text (DAFTAR ISI)
3_daftarisi.pdf Download (132kB) | Preview |
|
|
Text (BAB I)
4_bab1.pdf Download (164kB) | Preview |
|
Text (BAB II)
5_bab2.pdf Restricted to Registered users only Download (548kB) | Request a copy |
||
Text (BAB III)
6_bab3.pdf Restricted to Registered users only Download (3MB) | Request a copy |
||
Text (BAB IV)
7_bab4.pdf Restricted to Registered users only Download (1MB) | Request a copy |
||
Text (BAB V)
8_bab5.pdf Restricted to Registered users only Download (123kB) | Request a copy |
||
Text (DAFTAR PUSTAKA)
9_daftarpustaka.pdf Restricted to Registered users only Download (149kB) | Request a copy |
Abstract
INDONESIA: Dalam era perkembangan teknologi yang pesat, konsep Internet of Things (IoT) telah memberikan kontribusi baru dalam meningkatkan kualitas hidup melalui aplikasi yang terhubung dengan alat semacam sensor. Implementasi teknologi sensor IoT dapat digunakan efektif sebagai contohnya dalam memonitor kesehatan untuk mencegah risiko gangguan penyakit. Salah satu implementasi nya yaitu sistem monitoring postur tubuh saat duduk, yang penting untuk mencegah masalah kesehatan seperti gangguan muskuloskeletal yang umum terjadi akibat postur tubuh yang kurang tepat. Penelitian ini mengembangkan sebuah prototipe aplikasi monitoring postur tubuh berbasis flex sensor yang menerapkan algoritma Kalman Filter. Prototipe ini menggunakan sensor fleksibel yang dipasang pada perangkat wearable, mampu mendeteksi perubahan lengkungan posisi tubuh pengguna. Data dari sensor ini diproses melalui algoritma Kalman Filter untuk mengurangi fluktuasi data yang terjadi pada sensor. Hasil eksperimen menunjukkan bahwa setelah penerapan algoritma Kalman Filter, tingkat Root Mean Squared Error (RMSE) menurun secara signifikan, ini menandakan adanya ketepatan pengukuran postur tubuh dalam kondisi yang baik maupun buruk. ENGLISH: In an era of rapid technological development, the concept of the Internet of Things (IoT) has made a new contribution in improving the quality of life through applications connected to devices such as sensors. The implementation of IoT sensor technology can be used effectively, for example, in monitoring health to prevent the risk of disease. One implementation is a body posture monitoring system when sitting, which is important to prevent health problems such as musculoskeletal disorders which commonly occur due to inappropriate body posture. This research develops a prototype of a flex sensor-based body posture monitoring application that applies the Kalman Filter algorithm. This prototype uses a flexible sensor installed on a wearable device, capable of detecting changes in the curvature of the user's body position. Data from this sensor is processed through the Kalman Filter algorithm to reduce data fluctuations that occur on the sensor. The experimental results show that after applying the Kalman Filter algorithm, the Root Mean Squared Error (RMSE) level decreased significantly, this indicates the accuracy of body posture measurements in both good and bad conditions.
Item Type: | Thesis (Sarjana) |
---|---|
Uncontrolled Keywords: | Internet of Things (IoT); Ubiquitous Computing; Sensor Lengkungan; Aplikasi Kesehatan Preventif; Monitoring Postur Tubuh; Algoritma Kalman Filter |
Subjects: | Data Processing, Computer Science Data Processing, Computer Science > Computer Science Education Numerical Analysis > Algorithms Technology, Applied Sciences |
Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
Depositing User: | Aka Fadila |
Date Deposited: | 17 Sep 2024 02:00 |
Last Modified: | 17 Sep 2024 02:00 |
URI: | https://digilib.uinsgd.ac.id/id/eprint/95380 |
Actions (login required)
View Item |