Sistem Presensi Pegawai Menggunakan RFID Dilengkapi Sistem Optimasi Pembacaan Sensor Suhu Menggunakan Metode Kalman Filter Untuk Mencegah Penularan Covid-19

Ekhaputera, Rafi Pramasukma (2021) Sistem Presensi Pegawai Menggunakan RFID Dilengkapi Sistem Optimasi Pembacaan Sensor Suhu Menggunakan Metode Kalman Filter Untuk Mencegah Penularan Covid-19. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pada akhir Desember 2019 seluruh dunia digemparkan oleh pandemi Corona virus deseases (Covid-19). Covid-19 merupakan gejala virus yang menyerang pernapasan manusia. Salah satu gejala Covid-19 yang paling umum dialami penderita adalah Demam. Sistem presensi yang digunakan saat ini masih adanya kontak fisik antar pegawai dan belum ada pengecekkan suhu tubuh pada alat presensi. Pada tugas akhir ini sistem presensi yang dilengkapi dengan sensor suhu GY-906-BCC digunakan sebagai alat presensi sekaligus pengecekkan suhu. Sensor suhu GY-906-BCC memiliki kekurangan yaitu kesalahan pembacaan yang terlalu tinggi serta adanya noise yang mengganggu pembacaan sensor tersebut. Dalam hal ini perlunya metode kalman filter dapat mengurangi noise dalam pembacaan sensor GY-906-BCC agar pembacaan sensor lebih stabil. Keberhasilan Kalman filter dalam menghilangkan noise ditentukan oleh nilai R yang disebut kovarian noise pengukuran dan Q yang disebut kovarian noise proses. Pemilihan atau penggunaan nilai R dan Q dapat meningkatkan performa Kalman filter dalam menghilangkan noise. Pada percobaan yang dilakukan pembacaan sensor suhu GY-906-BCC dilakukan 5 kali percobaan dengan menggunakan metode kalman filter. Metode kalman filter dapat mengurangi noise pada sensor suhu GY-906-BCC dengan nilai sebesar R=100 dan Q=0,1. Maka metode tersebut mampu meng-optimasi pembacaan sensor suhu GY-906-BCC dan dapat digunakan sebagai mengukur suhu tubuh manusia dengan tepat dan akurat. ===================================================================================================== At the end of December 2019 the whole world was shocked by the Corona virus disease (Covid-19) pandemic. Covid-19 is a symptom of a virus that attacks human respiration. One of the most common symptoms of COVID-19 experienced by sufferers is fever. The presence system used today still has physical contact between employees and there is no body temperature checking on the attendance device. In this final project, a presence system equipped with a temperature sensor GY-906-BCC is used as a presence tool as well as a temperature check. The GY-906-BCC temperature sensor has drawbacks, namely the reading error is too high and the noise that interferes with the sensor reading. In this case, the need for the kalman filter method can reduce noise in the GY-906-BCC sensor readings so that the sensor readings are more stable. The success of the Kalman filter in removing noise is determined by the value of R which is called the covariance of the measurement noise and Q, which is called the covariance of the process noise. The selection or use of R and Q values can improve the performance of the Kalman filter in removing noise. From the tests that have been carried out the kalman filter method reduces noise on the GY-906-BCC temperature sensor with a value of R = 100 and Q = 0.1. So this method is able to optimize the reading of the GY-906-BCC temperature sensor and can be used to measure human body temperature precisely and accurately.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Sistem presensi, Sensor GY-906-BCC, suhu, kalman filter Presence system, GY-906-BCC sensor, temperature, linear regression, Kalman Filter
Subjects: T Technology > T Technology (General) > T55 Industrial Safety
T Technology > T Technology (General) > T57.5 Data Processing
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK105.8883 Web authoring software (include web server)
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.888 Web sites--Design. Web site development.
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7888.3 Digital computers
Divisions: Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User: Rafi Pramasukma Ekhaputera
Date Deposited: 04 Sep 2021 02:24
Last Modified: 04 Sep 2021 02:24
URI: https://repository.its.ac.id/id/eprint/91004

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