Proceedings of the First International Conference on Social Science, Humanity, and Public Health (ICOSHIP 2020)

The Implementation of Big Data Technology in Virtual Machines for Mapping 2019-nCoV Pandemic on the Students of Information Technology

Authors
Surateno, Ery Setiyawan Jullev Atmadji
Corresponding Author
Surateno
Available Online 2 January 2021.
DOI
https://doi.org/10.2991/assehr.k.210101.009How to use a DOI?
Keywords
covid19, virtual machine, e-learning, machine learning
Abstract
The spread of Covid-19 has influenced changes in human behavior and paradigm including in teaching and learning process. The teaching and learning process has now been replaced by E-Learning models which offer flexibility for both teachers and students. Current learning process can be accessed by students from different places and not necessarily gather in one room. However, this raises a new problem, namely the difficulty of tracking the scattered students when they return to campus. One way to overcome this problem is to use a big data approach combined with a virtual machine to recognize and detect these students. In this approach, the results of tracking students with server computer resources are up to 15% smaller than using non virtual machines. This is a new approach to data processing.
Open Access
This is an open access article distributed under the CC BY-NC license.

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TY  - CONF
AU  - Surateno
AU  - Ery Setiyawan Jullev Atmadji
PY  - 2021
DA  - 2021/01/02
TI  - The Implementation of Big Data Technology in Virtual Machines for Mapping 2019-nCoV Pandemic on the Students of Information Technology
BT  - Proceedings of the First International Conference on Social Science, Humanity, and Public Health (ICOSHIP 2020)
PB  - Atlantis Press
SP  - 37
EP  - 40
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210101.009
DO  - https://doi.org/10.2991/assehr.k.210101.009
ID  - Surateno2021
ER  -