Rancang Bangun Sistem Deteksi Masker dan Suhu Badan Sebagai Prasyarat Absensi Berbasis Internet of things

sri anggraeni kadiran

Abstract


The mask and body temperature detection system for public places is still operated manually. The system was found not to adjust to the conditions of office employees, which required them to always be on guard and check the body temperature of every employee who would enter the office. Therefore, a mask and body temperature detection system was designed as a prerequisite for internet of things-based attendance that can make it easier for office employees to check the body temperature of everyone who will work, and so that employees can be disciplined in time. This system requires a temperaturesensor to detect the body temperature of people who will enter. A person's body temperature is said to be normal if it is lessthan 37.20C. If the temperature exceeds 37.20 C, then a person cannot take attendance. In addition to having a normal body temperature, the second requirement must be met, namely passing mask detection. Someone must wear a mask before entering the room, before taking attendance using a fingerprint. Arduino Uno will send data from the temperature sensor to the database and a 16x2 LCD, so that the system can be connected to the web which can be monitored by the administrator to get data on the number of office employees based on body temperature. In addition, a Raspberry Pi is used which will senddata from the webcam as a result of the mask detection image processing. The results of this final project indicate that the data sent to the web is in accordance with the data based on testing tools.


Keywords


detection

Full Text:

PDF

References


Ajang, Rahmat. 2015. “Cara Simple Program LCD I2C 16x2 Menggunakan Arduino - Kelas Robot.”

Ajie. 2016. “Bekerja Dengan I2C LCD Dan Arduino – Saptaji.Com.” Saptaji.Com.

Algonz D.B. Raharja. 2022. “Machine Learning: Pengertian, Cara Kerja, Dan 3 Metodenya!”

Asfihan, Akbar. 2022. “Firebase Adalah : Cara Kerja, Sejarah, Manfaat Dan Kelebihan.” 9 Juni.

Efendi, Yoyon. 2018. “Internet Of Things (Iot) Sistem Pengendalian Lampu Menggunakan Raspberry Pi Berbasis Mobile.” Jurnal Ilmiah Ilmu Komputer 4(2):21–27. doi: 10.35329/jiik.v4i2.41.

Hermawati, Fajar Astuti, and Restin Alfinda Zai. 2021. “Sistem Deteksi Pemakaian Masker Menggunakan Metode Viola-Jones Dan Convolutional Neural Networks (CNN).” Proceeding KONIK (Konferensi Nasional Ilmu Komputer) 5:182–87.

Lina, Qolbiyatul. 2019. “Apa Itu Convolutional Neural Network? | by QOLBIYATUL LINA | Medium.” Medium.Com 1–17.

Malik, Muhammad Hasan Abdul. 2018. “Cara Menggunakan Keypad 4x4 Matrix Di Arduino.” Blogspot.Com.

Nikmatuzaroh, R. .. dan N. Maziyyah. 2019. “済無No Title No Title No Title.” Skripsi.




DOI: http://dx.doi.org/10.26623/jprt.v18i2.6948

Refbacks

  • There are currently no refbacks.


View My Stats

Penerbit

 

Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Semarang

Alamat Redaksi:

Jl.Soekarno-Hatta, Tlogosari, Semarang, Jawa Teangah, Indonesia 50196 Telp: 024-6702757 psw: 8302 Fax: 024-6702272 e-mail: jprt@usm.ac.id

Creative Commons License
This work is licensed under a  Creative Commons Attribution 4.0 International License.