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Comparison of singular spectrum analysis forecasting algorithms for student\s academic performance during COVID-19 outbreak

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General Information Cached
Title
Comparison of singular spectrum analysis forecasting algorithms for student\s academic performance during COVID-19 outbreak
Type
Article
Main Author
Shazlyn Milleana Shaharudin
Additional Authors
  • Muhammad Fakhrullah Mohd Fuad
  • Nor Ain Maisarah Samsudin
  • Muhammad Fareezuan Zulfikri
Subject
H Social Sciences
ISSN
2394-5443
Language Code
eng
Bibliographic Details
Place of Production
Tanjung Malim
Publisher
Fakulti Sains dan Matematik
Year of publication
2021
Notes
International Journal of Advanced Technology and Engineering Exploration
Degree Type
Others
Corporate Name
Universiti Pendidikan Sultan Idris
HTTP Link
Access Web Resource

Abstract

Due to the spread of COVID-19 that hit Malaysia, all academic activities at educational institutions including universities had to be carried out via online learning. However, the effectiveness of online learning is remains unanswered. Besides, online learning may have a significant impact if continued in the upcoming academic sessions. Therefore, the core of this study is to predict the academic performance of undergraduate students at one of the public universities in Malaysia by using Recurrent Forecasting-Singular Spectrum Analysis (RF-SSA) and Vector Forecasting-Singular Spectrum Analysis (VF-SSA). The key concept of the predictive model is to improve the efficiency of different types of forecast model in SSA by using two parameters which are window length (L) and number of leading components (r). The forecasting approaches in SSA model was based on the Grading Point Assessments (GPA) for undergraduate students from Faculty Science and Mathematics, UPSI via online classes during COVID-19 outbreak. The experiment revealed that parameter L= 11 (T/20) has the best prediction result for RF-SSA model with RMSE value of 0.19 as compared to VF-SSA of 0.30. This signifies the competency of RF-SSA in predicting the students? academic performances based on GPA for the upcoming semester. Nonetheless, an RF-SSA algorithm should be developed for higher effectivity of obtaining more data sets including more respondents from various universities in Malaysia. ? 2021 Muhammad Fakhrullah Mohd Fuad et al.

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