E3S Web Conf.
Volume 317, 2021The 6th International Conference on Energy, Environment, Epidemiology, and Information System (ICENIS 2021)
|Number of page(s)||11|
|Section||Information System Management and Environment|
|Published online||05 November 2021|
- Y. Zhang, F. Qin, dan J. Liu, “Improving education equality and quality: Evidence from a natural experiment in China,” Int. J. Educ. Dev., vol. 70, Okt (2019) [Google Scholar]
- A. Voutilainen, T. Saaranen, dan M. Sormunen, “Conventional vs. e-learning in nursing education: A systematic review and meta-analysis,” Nurse Educ. Today, vol. 50, hal. 97–103, (2017) [Google Scholar]
- S. Caskurlu, Y. Maeda, J. C. Richardson, dan J. Lv, “A meta-analysis addressing the relationship between teaching presence and students’ satisfaction and learning,” Comput. Educ., vol. 157, no. May, hal. 103966, (2020) [Google Scholar]
- O. Belash, M. Popov, N. Ryzhov, Y. Ryaskov, S. Shaposhnikov, dan M. Shestopalov, “Research on University Education Quality Assurance: Methodology and Results of Stakeholders’ Satisfaction Monitoring,” Procedia - Soc. Behav. Sci., vol. 214, no. June, hal. 344–358, (2015) [Google Scholar]
- ISO, “INTERNATIONAL STANDARD Educational organizations — Management systems for educational organizations — Requirements with guidance for use,” vol. 2018, (2018) [Google Scholar]
- Y. Wang, “Microprocessors and Microsystems Educational management system of colleges and universities based on embedded system and artificial intelligence,” Micro process. Microsyst., vol. 82, no. January, hal. 103884, (2021) [Google Scholar]
- H. Ajpru, S. Wongwanich, dan P. Khaikleng, “Design of Educational Quality Assurance System for Driving Policy of Educational Reform in Thailand: Theory-based Evaluation,” Procedia - Soc. Behav. Sci., vol. 116, no. 22, hal. 1416–1422, (2014) [Google Scholar]
- S. Thaker dan V. Nagori, “Analysis of Fuzzification Process in Fuzzy Expert System,” Procedia Comput. Sci., vol. 132, hal. 1308–1316, (2018) [Google Scholar]
- A. Nugroho dan A. Nugroho, “ScienceDirect Procedia ScienceDirect ScienceDirect Mobile Expert System Using Fuzzy Tsukamoto for Diagnosing Cattle Disease Mobile Expert System Using Fuzzy Tsukamoto for Diagnosing Cattle Disease,” Procedia Comput. Sci., vol. 116, no. Iccsci, hal. 27–36, (2017) [Google Scholar]
- G.-J. Hwang, H.-Y. Sung, S.-C. Chang, dan X.-C. Huang, “A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors,” Comput. Educ. Artif. Intell., vol. 1, no. August, hal. 100003, (2020) [Google Scholar]
- S. Suryono, A. Khuriati, dan T. Mantoro, “A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation,” Cogent Eng., vol. 6, no. 1, hal. 1–19, (2019) [Google Scholar]
- S. Sava, C. Borca, dan L. Danciu, “Models of Quality Assurance in Evaluation and Validation of Competencies, for an Easier Access to Higher Education,” Procedia - Soc. Behav. Sci., vol. 142, hal. 176–182, (2014) [Google Scholar]
- Dkk Mel Barracliffe, Lisa Gardner, “Systems Development Life Cycle (SDLC) Methodology,” hal. 1–9, (2009) [Google Scholar]
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