RANCANG BANGUN SISTEM PRESENSI BERBASIS IOT
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Stephanie Imelda Pella(1*)
Universitas Nusa Cendana
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Frans Likadja(2)
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Molina Odja(3)
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Wenefrida T Ina(4)
(*) Corresponding Author
Abstract
The purpose of this research is to design and implement an attendance system based on internet of things (IoT) . The proposed system integrated two types of attendance systems, face recognition based attendance system (FRA) and fingerprint-based attendance system (FPA), with a central server. The FRA was developed in a Raspberry Pi mini-computer using Python programming language and Openc CV library. The FPA, on the other hand, was developed using Node MCU ESP8266 and Fingerprint scanner AS608 with Adafruit Fingerprint library. Both FRA and FPA are connected to a web server with a database engine through the internet connection and sensing attendance data using the HTTP_POST method. The server was developed using Apache Webserver, PHP programming language, and MySQL database engine. The server serves two main purposes, which are to record the attendance data sent by the FPA and FRA, and generate an attendance report based on the user query. The system testing was done in a local network. The result showed that both the subsystems and the integrated system worked well
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References
M. Richardson and S. Wallace, Getting started with raspberry PI: " O'Reilly Media, Inc.", 2012.
E. Upton and G. Halfacree, Raspberry Pi user guide: John Wiley & Sons, 2014.
R. Pi, "Raspberry pi 3 model b," online].(https://www. raspberrypi. org, 2015.
S. A. Arduino, "Arduino," Arduino LLC, 2015.
M. Schwartz, Internet of Things with ESP8266: Packt Publishing Ltd, 2016.
A. Kaehler and G. Bradski, Learning OpenCV 3: computer vision in C++ with the OpenCV library: " O'Reilly Media, Inc.", 2016.
J. V. Dillon, I. Langmore, D. Tran, E. Brevdo, S. Vasudevan, D. Moore, et al., "Tensorflow distributions," arXiv preprint arXiv:1711.10604, 2017.
H. F. Lami, S. Tena, B. H. Manafe, J. F. Bowakh, N. Nursalim, and S. Sudirman, "Rancang Bangun Sistem Pengenalan Wajah Daftar Pencarian Orang (Dpo) Berbasis Jaringan Saraf Tiruan," Media Elektro, pp. 129-133, 2019.
H. F. Lami and S. I. Pella, "Implementasi Deteksi dan Pengenalan Wajah pada Sistem Ujian Online Menggunakan Metode Deep Learning Berbasis Raspberry Pi," Media Elektro, pp. 89-92, 2019.
R. A. Doga, H. F. Lami, and S. I. Pella, "SISTEM IDENTIFIKASI NOMINAL UANG LOGAM MENGGUNAKAN TENSORFLOW DAN CONVOLUTIONAL NEURAL NETWORK BERBASIS RASPBERRY PI," SAINSTEK, vol. 4, pp. 503-511, 2019.
I. W. Muttaqin and A. Rahman, "Sistem Presensi Berbasis RFID Menggunakan Raspberry Pi 3," Buletin Ilmiah Sarjana Teknik Elektro, vol. 1, pp. 27-34, 2019.
M. B. Setyawan, A. F. Cobantoro, and A. Prasetyo, "PROTOYPE MONITORING PRESENSI SISWA MENGGUNAKAN FINGER PRINT DENGAN KENDALI RASPBERRY PI," JURNAL TEKNIK INFORMATIKA, vol. 13, pp. 21-30, 2020.
R. Prathivi and Y. Kurniawati, "SISTEM PRESENSI KELAS MENGGUNAKAN PENGENALAN WAJAH DENGAN METODE HAAR CASCADE CLASSIFIER," Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, vol. 11, pp. 135-142, 2020.
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