Analisis Kelayakan Calon Pengawas Sekolah Dengan Menggunakan Metode Data Mining Decision Tree

Abstract

School supervisors have an important role in the world of education whose job is to improve the quality of education. Qualifications of competent school supervisors are needed to master academic performance and management of educational institutions. In the implementation of the selection of prospective school supervisors, each participant must meet the requirements of the level of education, class, age, years of service of teachers, and educator certificates. To determine graduation, certain conditions are prepared that are used as the basis for the assessment. The C4.5 algorithm used in the Decision Tree data mining method of data classification that produces one decision tree. The results of the dataset test using the C4.5 algorithm to determine the feasibility of prospective school supervisors using Rapidminer tools have good values, the accuracy calculation is 95.07%, the precision calculation is 100%, and the recall calculation is 82.28 %. The resulting knowledge is used as a reference in the eligibility of prospective school supervisors.