Penerapan Decision Tree C4.5 Dalam Memprediksi Predikat Terbaik Di Madrasah Ta'hiliyah Ibrahimy
Year: 2025
Type: article
Abstract: To improve the evaluation process in assessing student progress, predicting the best grades plays a crucial role in enhancing the quality of education. By identifying the top-performing students, educational institutions can refine their teaching methods and create targeted strategies to foster better learning outcomes. This step is vital for ensuring that the learning process aligns with the institution's goals to produce highly skilled and knowledgeable students. In this research, we focused on utilizing the C4.5 algorithm, a widely recognized decision tree method in data mining, to predict student achievements. The C4.5 algorithm is known for its ability to classify and uncover hidden patterns within datasets, making it a powerful tool for educational data analysis. Through this approach, we aim to analyze the factors influencing student success and provide actionable insights for educators and administrators. The study was conducted on students from Madrasah Ta’hiliyah Ibrahimy, where we applied the decision tree algorithm to predict the best grades based on historical academic data. The experiment resulted in three distinct rules or patterns derived from the data, with an overall accuracy of 74.17%. These findings demonstrate the potential of data-driven approaches in supporting academic decision-making and guiding future interventions to further enhance student performance.
Source: Jurnal Ilmiah Multidisiplin Ilmu
DOI: 10.69714/be4q6n31
Authors: Ahmad Huday, Zaehol Fatah
Institution: Universitas Ibrahimy
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4407063735