IO, Surabaya – The Covid-19 pandemic has caused face-to-face teaching and learning activities to be halted, for fear of further spread of Covid-19 clusters in schools in yellow and green zones once the new normal was implemented. Beginning with this challenge, three students of the Instrumentation Engineering Department, Vocational Faculty, Sepuluh Nopember Institute of Technology (ITS) Surabaya who are members of the Insforty Team, namely Mohammad Jailani, Egik Ardiatmajaya, and Nanak Cito Tetuko, initiated an attendance recording tool called Presentar.
According to Mohammad Jailani, Chair of the Insforty Team, this innovation is based on concerns about the spread of Covid-19 in educational sectors. “To prevent the spread of Covid-19 in schools, a safe and automatic health protocol is needed,” said the 2018 student who is usually called Jailani, in a release received by the Independent Observer, Monday (8/2/2021).
The Insforty Team under the guidance of Brian Raafi’u worked hard for two months to create Presentar. The fruit of their efforts was a Second-Place win in the National Scientific Writing Competition, Borneo Scientific Fair 4, held by UKM PP Lisma, Tanjungpura University, Pontianak, West Kalimantan, last January. In this competition, Insforty Team managed to outperform 10 other finalists, selected from 56 national papers.
Presentar works by helping to avoid the necessity of physical contact between humans, in line with health protocols in the education sector. This tool can record attendance, detecting body temperature because it is equipped with a thermal detector, issue hand sanitizers automatically, in addition to tracking travel history through Global Positioning System (GPS) tracking and monitoring through a system design based on IoT (Internet of Things). Presentar is equipped with masked face recognition so that attendance can still be taken, even though students are wearing masks and without needing to touch any objects. The five stages of the masked face recognition process are called the Multi-Task Cascaded Convolution Neural Network (MTCNN), namely Facial Image Acquisition, Masked Face Detection Using MTCNN, Image Post-processing, Feature Extraction using FaceNet, and Face Verification Using SVM. With this stage, a person’s face can be recognized automatically and accurately.
“The hope is that before entering school, students will have guaranteed sterility through this automatic health protocol. Presentar is very suitable to be applied to the education sector in the new normal era such as the one in force now,” said the alumnus of MA Model Zainul Hasan, Genggong, Probolinggo.
Jailani hopes that in the future this tool can work more effectively for an attendance monitoring system in the new normal era. “Hopefully this system can also be applied in various sectors such as industry and offices,” he said. )