Regularized Ordinal Regression with LASSO: Identifying Factors in Students' Public Speaking Anxiety at Universitas Negeri Padang
DOI:
https://doi.org/10.24036/ujsds/vol2-iss4/316Keywords:
Public speaking anxiety, ordinal regression, LASSO, variable selection, multicollinearityAbstract
Public speaking anxiety is a common issue faced by students, particularly in academic settings. It may arise from a range of factors, including humiliation, physical appearance, preparation, audience interest, personality traits, rigid rules, unfamiliar role, negative result, and mistakes. This research seeks to determine the factors influencing different levels of public speaking anxiety among students at Universitas Negeri Padang through the application of ordinal regression with LASSO regularization. This method allows for automatic selection of significant variables and addressesmulticollinearity issues. The results indicate that eight factors influence low public speaking anxiety levels, while only six factors impact high public speaking anxiety levels. The ordinal regression model with LASSO penalty demonstrates good performance in classifying public speaking anxiety levels, achieving an accuracy of 71.33%. This study is expected to help students and educators better understand and manage public speaking anxiety, thereby enhancing public spekaing competence among students
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Copyright (c) 2024 natasyalinggaa Natasya Dwi Ovalingga, Nonong Amalita, Yenni Kurniawati, Zamahsary Martha
This work is licensed under a Creative Commons Attribution 4.0 International License.