Implementasi Penerapan Metode C4.5 dan Naïve Bayes Dalam Tingkat Kelulusan Akreditasi Lembaga PAUD Pada Badan Akreditasi Nasional

Abstract

Education from an early age is one way to stimulate children's potential. This is explained in the Law of the Republic of Indonesia Number 20 of 2003 concerning the National Education System which states that Early Childhood Education (PAUD) is a coaching effort aimed at children from birth to the age of six which is carried out through the provision of educational stimuli to help growth and physical and spiritual development so that children have readiness to enter further education. The National Accreditation Board for Early Childhood Education and Non-Formal Education, hereinafter referred to as BAN PAUD and PNF, is an independent evaluation body that determines the feasibility of PAUD and PNF programs and/or units. BAN PAUD and PNF were formed based on Permendikbud Number 52 of 2015 concerning the National Accreditation Board for Early Childhood Education and Non-Formal Education which is a substitute for Permendikbud 59 of 2012. Improving the quality of the implementation of PAUD and PNF Accreditation can be done by increasing the availability of non-formal education accreditation services. Other things that can be done to improve the quality of the implementation of PAUD accreditation are by providing certainty and guarantee of obtaining non-formal education accreditation services and improving a reliable governance system in ensuring the implementation of non-formal education accreditation services. This study uses data mining techniques in predicting the accreditation status of PAUD education units. First, preprocessing is used to get a quality dataset. Second, the data is processed to get a series of predictions. In this step, two data mining algorithms are applied, namely the Naïve Bayes Algorithm and the C4.5 Algorithm with the aim of knowing the performance of the two algorithms with a greater level of accuracy will be recommended in solving the problem of predicting the accreditation of PAUD education units in BAN PAUD and PNF DKI Jakarta Province. Then the third, the results will be in the Conffusion Matrix to validate the accuracy of the prediction results. And the results of the assessment show that the C4.5 and Naïve Bayes Algorithm methods can be used to predict the accreditation status of PAUD education units with an accuracy of 99.00%