Dynamic Monitoring and Assessment for Digital Transformation in Higher Education
- DOI
- 10.2991/assehr.k.210421.001How to use a DOI?
- Keywords
- Information Technology, Dynamic Monitoring, Assessment, Machine Learning, Higher Education
- Abstract
The development of information technology applied to college institutions is experiencing rapid growth. Information technology can solve problems faced in educational institutions. Universities are increasing the use of information and digital technologies for improved service, data management, and accurate reporting. Monitoring and assessment are an essential part of college development. The parameters used in monitoring and assessment use a parameter on the strategic plan of the college. The comparative study of the strategic plan is targeted at two universities that have different characteristics, namely public universities and Islamic state universities. The method used in building dynamic monitoring and assessment uses machine learning. Parameters in monitoring and assessment include Tri Dharma Higher Education such as research, education, and community development. Based on these problems can be formulated implementation of dynamic monitoring and assessment for digital transformation in Higher Education as well as prototype models of dynamic monitoring and assessment based on machine learning. The results obtained show that parameter testing yields an average of 78%. This indicates that the level of accuracy using machine learning can implement dynamic monitoring and assessment in digital transformation at higher education.
- Copyright
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Supriyono AU - Muhamad Faisal PY - 2021 DA - 2021/04/22 TI - Dynamic Monitoring and Assessment for Digital Transformation in Higher Education BT - Proceedings of the International Conference on Engineering, Technology and Social Science (ICONETOS 2020) PB - Atlantis Press SP - 1 EP - 7 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.210421.001 DO - 10.2991/assehr.k.210421.001 ID - 2021 ER -