Job Market Test Attendance System With Health Protocols  Using The Internet Of Things

Andriyan Dwi Putra; Lukman Hakim; Ali Mustopa

doi:10.32520/stmsi.v12i3.2910

Job Market Test Attendance System With Health Protocols Using The Internet Of Things

Andriyan Dwi Putra, Lukman Hakim, Ali Mustopa

Abstract

During the transitional period related to the coronavirus outbreak, the need for jobs began to increase. The number of prospective workers who will apply for a job in a company by doing a selection test at the Job Exchange. On the other hand, to suppress the spread of this epidemic, the interaction between Job Exchange officers and prospective job applicants must be limited. So by creating a Job Exchange Test attendance system according to health protocols with the Internet of Things devices, it can be used to limit the interaction of prospective job applicants with job exchange officers. This system was built using the Waterfall Model Software Development Life Cycle method, by utilizing the ESP8266 microcontroller components, the MFRC522 module, and the MLX90614 sensor which will support the performance of this system. The results of this study are taboos for prospective job applicants who have an illegal condition or have a temperature above normal, may not enter the room without interacting directly with the officer, but the device will sound a buzzer notification and a warning message will be sent from the microcontroller and received by the officer via telegram. In this study, a comparison was made to obtain the ideal distance for scanning body temperature at various different distances, and the results of the comparison obtained the smallest percentage error value of 0.027% at a distance of 3 cm.

Full Text:

PDF

References

A. Irawati et al., “Panduan Pelaksanaan Protokol Kesehatan,” Satgas Penanganan COVID-19, 2021.

B. Chen, H. Zhong, Y. Ni, L. Liu, J. Zhong, and X. Su, “Epidemiological Trends of Coronavirus Disease 2019 in China,” Front. Med., vol. 7, May 2020, doi: 10.3389/fmed.2020.00259.

World Health Organization, “Transmission of SARS-CoV-2: implications for infection prevention precautions,” who.int, 2020.

Kemenkes, “Bagaimana manusia bisa terinfeksi COVID-19,” infeksiemerging.kemkes.go.id.

C. Sun and Z. Zhai, “The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission,” Sustain. Cities Soc., vol. 62, no. July, p. 102390, 2020, doi: 10.1016/j.scs.2020.102390.

G. Ayu, “Protokol Pengukuran Suhu Tubuh Banyak yang Salah dan Sering Dilakukan, Ini Faktanya,” gsilab.id, 2021.

M. Ismail, A. D. Prasetyowati, and J. P. Hapsari, “Desain dan Implementasi Akuisisi Data Suhu Murid Sekolah Berbasis Arduino Untuk Monitoring Kesehatan Komunal,” J. Nas. Tek. ELEKTRO, vol. 8, no. 2, p. 58, Jul. 2019, doi: 10.25077/jnte.v8n2.640.2019.

M. Safitri and G. A. Dinata, “NON-CONTACT THERMOMETER BERBASIS INFRA MERAH,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 10, no. 1, pp. 21–26, Apr. 2019, doi: 10.24176/simet.v10i1.2647.

Helmy Yudhistira Putra and Utomo Budiyanto, “Rancang Bangun Pengukur Suhu Tubuh Dengan Multi Sensor Untuk Mencegah Penyebaran Covid-19,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 3, pp. 543–549, Jun. 2021, doi: 10.29207/resti.v5i3.2931.

N. Hidayati and S. Sismadi, “Application of Waterfall Model In Development of Work Training Acceptance System,” INTENSIF J. Ilm. Penelit. dan Penerapan Teknol. Sist. Inf., vol. 4, no. 1, pp. 75–89, Feb. 2020, doi: 10.29407/intensif.v4i1.13575.

O. J. Okesola, A. A. Adebiyi, A. A. Owoade, O. Adeaga, O. Adeyemi, and I. Odun-Ayo, “Software Requirement in Iterative SDLC Model,” 2020, pp. 26–34. doi: 10.1007/978-3-030-51965-0_2.

Y. Bassil, “A Simulation Model for the Waterfall Software Development Life Cycle,” May 2012, [Online]. Available: http://arxiv.org/abs/1205.6904

S. Herawati, Y. D. P. Negara, H. F. Febriansyah, and D. A. Fatah, “Application of the Waterfall Method on a Web-Based Job Training Management Information System at Trunojoyo University Madura,” E3S Web Conf., vol. 328, p. 04026, Dec. 2021, doi: 10.1051/e3sconf/202132804026.

E. Pawan, A. Jasuma, A. Y. Arif, and K. Kusrini, “Sistem Pendukung Keputusan Menentukan Bibit Padi Terbaik Menggunakan Metode Gap Kompetensi,” SISFOTENIKA, vol. 10, no. 1, p. 24, Jan. 2020, doi: 10.30700/jst.v10i1.511.

S. Ergasheva and A. Kruglov, “Software Development Life Cycle early phases and quality metrics: A Systematic Literature Review,” J. Phys. Conf. Ser., vol. 1694, no. 1, p. 012007, Dec. 2020, doi: 10.1088/1742-6596/1694/1/012007.

W. O. S. N. Alam, A. N. Aliansyah, F. E. Larobu, L. Mulyawati, A. Asminar, and I. Galugu, “Tingkat akurasi Sensor AMG8833 dan Sensor MLX90614 dalam Mengukur Suhu Tubuh,” JTEV (Jurnal Tek. Elektro dan Vokasional), vol. 8, no. 1, p. 169, May 2022, doi: 10.24036/jtev.v8i1.114543.

Y. Mukhammad and A. S. Hyperastuty, “Sensitivitas Sensor MLX90614 Sebagai Alat Pengukur Suhu Tubuh Tubuh Non-Contact Pada Manusia,” Indones. J. Prof. Nurs., vol. 1, no. 2, p. 51, Mar. 2021, doi: 10.30587/ijpn.v1i2.2339.

DOI: https://doi.org/10.32520/stmsi.v12i3.2910

Article Metrics

Abstract view : 174 times
PDF - 60 times

Refbacks

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

Username
Password
Remember me