Conference paper 2020

Simulation of SAW-based CIPP Evaluation Model Calculation in Determining Improvement Priority for E-Learning Services

WA
Wisna Ariawan, I. Putu
 GM
Giri, Made Kurnia Widiastuti
 DD
Divayana, Dewa Gede Hendra
4th International Conference on Vocational Education and Training, ICOVET 2020
Conference · pp. 24-29
Abstract

This research has the main objective to explain the steps of the SAW (Simple Additive Weighting) method calculation process used to determine one improvement priority aspect in CIPP (Context-Input-Process-Product) evaluation model so the e-learning services more effectiveness. This research used a quantitative approach to obtain the lowest preference value from the evaluation aspect of the CIPP model. The research subjects who were involved in this research were 64 people. The tool used in collecting simulation data was questionnaires. This research was conducted in several health colleges in Bali Province. The technique was used to analyze the data from the SAW method calculation was the technique of the lowest preference value searching. This research result showed the accuracy of the SAW-based CIPP model calculation in determining the priority aspect of improvement with a preference value was 0.37192. © 2020 IEEE.

Keywords

Author Keywords

Simulation E-learning CIPP evaluation model SAW

Index Keywords

E-learning Learning systems Apprentices Quantitative approach Surveys Research subjects Process products Simple additive weighting Evaluation modeling Calculation process E-learning services Model calculations
Author Affiliations
Department of IT Education, Universitas Pendidikan Ganesha, Bali, Indonesia
Department of Mathematics Education, Universitas Pendidikan Ganesha, Bali, Indonesia
Department of Medicine, Universitas Pendidikan Ganesha, Bali, Indonesia
Funding & Acknowledgements
No funding information
References 10 References
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7 International Journal of Environmental Science Education, (2017)
8 Innovative Journal of Curriculum and Educational Technology, (2018)
9 Int J Pure Appl Math, (2018)
10 Bit Tech, (2018)
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