Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 5 No. 2 (2021): Article Research Volume 5 Number 2, April 2021

Measurement of e-school User Experience, Does it Support Blended Learning during the Covid-19 Pandemic ? : (Case Studies at Three Parent Schools LPKA Class I Palembang)

Febrianty, Febrianty (Unknown)
Hadiwijaya, Hendra (Unknown)
Octafian, D. Tri (Unknown)



Article Info

Publish Date
21 Apr 2021

Abstract

This study aims to measure the User Experience of e-school in supporting blended learning during the Covid-19 Pandemic. The object of this research is the parent school of LPKA Class I Palembang, namely: SDN 25, SMPN 22, and SMAN 11 Palembang. Because of this, all of the parent schools implemented an e-school web system adapted from the LPKA Class I Palembang filial e-school. The method used in this study was UEQ which was introduced by (Schrepp, 2018). The results of UEQ measurements on parent-school students show that: a). web e-school SDN 25 Palembang, on the scale of attractiveness, clarity, and accuracy are categorized as "above average" while the scale of efficiency, stimulation, and novelty are categorized as "good". b). web e-school SMPN 22 Palembang, on the scale of attractiveness, clarity, and efficiency are categorized as "above average" while the scale of accuracy and stimulation are categorized as "good". For novelty scale in the "Excellent" category. c). Web e-school of SMAN 11 Palembang, on a scale of attractiveness, efficiency, stimulation, and novelty is categorized as "good" while clarity and accuracy are categorized as "above average". For novelty scale in the "Excellent" category. Meanwhile, what parent-school teachers feel about the e-school web, on a scale of attractiveness, clarity, efficiency, accuracy, and novelty are categorized as "above average". Meanwhile, the other scale, stimulation, is categorized as "below average". So in other words, the web-adapted e-school from the LPKA Class I Palembang filial e-school as a whole has been able to support Blended-Learning learning during the Covid-19 Pandemic, although improvements still need to be made.

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Journal Info

Abbrev

sinkron

Publisher

Subject

Computer Science & IT

Description

Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial ...