Classification of Teacher Certification Eligibility Using the C4.5 Algorithm

Agnes Irene Silitonga; Mismauli Nainggolan; Tasya Arcinta; Yoakim Simamora; Ferry Indra Sakti H Sinaga

doi:10.63322/2ar4tf74

Authors

Agnes Irene Silitonga Universitas Negeri Medan https://orcid.org/0000-0003-0625-3714
Mismauli Nainggolan Universitas Negeri Medan
Tasya Arcinta Universitas Negeri Medan
Yoakim Simamora Universitas Negeri Medan
Ferry Indra Sakti H. Sinaga Universitas Negeri Medan

DOI:

https://doi.org/10.63322/2ar4tf74

Keywords:

Machine Learning, C4.5 Algorithm, Decision Tree , Classification , Teacher Certification Eligibility

Abstract

Determining teacher certification eligibility is a crucial process in improving the quality of education. The C4.5 algorithm is a decision tree-based machine learning algorithm. This algorithm offers a systematic approach to data analysis and provides accurate results for decision-making. This study aims to develop a predictive model using the C4.5 algorithm to assess teacher certification eligibility based on relevant data such as teaching experience, education, and competency exam results. This study reveals that the C4.5 algorithm is capable of producing transparent decision rules and enabling clear interpretation of the results. This research is expected to make a significant contribution to supporting a more objective and efficient teacher certification policy.