Application of Data Mining with C4.5 Algorithm to Identify Dominant Factors Determining Teacher Quality in Nias Utara Regency
Keywords:
Data Mining, C4.5, Teacher Quality, Nias Utara Regency, EducationAbstract
Teacher quality is a key determinant in improving the quality of education, which directly contributes to the increase of the Human Development Index (HDI). Nias Utara Regency, with an HDI of 66.42 in 2024 (BPS Nias Utara, 2025) still below the North Sumatra provincial average of 75.76 faces serious challenges in improving the quality of its teaching workforce. This study aims to identify the dominant factors influencing teacher quality in Nias Utara Regency by applying the C4.5 classification algorithm in data mining. Data were sourced from the official publication "Nias Utara Regency in Figures 2025", including attributes of teacher education level, employment status (civil servant/PPPK), student-teacher ratio, and availability of school facilities. The C4.5 algorithm was used to build a decision tree capable of separating the determining factors of teacher quality. The analysis results show that the Education Level attribute becomes the root node with the highest gain ratio value (0.845), followed by Employment Status (0.672) and Student-Teacher Ratio (0.431). These findings indicate that improving teachers' academic qualifications to bachelor's/master's levels and converting honorary staff into civil servants (ASN) are the top policy priorities. This research provides a practical data-driven contribution to decision-making for the Education Office and local government of Nias Utara Regency.
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