Analysis Using Random Tree And Random Forest With The Gini Index Algorithm On Data - nuranisah nuranisah (Jurnal Mantik, 2022)
(PPDB or Penerimaan Peserta Didik Baru )New Student Admission on the achievement path has been listed in the Minister of Education and Culture number 44 of 2019 in article 11 paragraphs 1 & 2, it is possible for new students who have achievements to not be able to enter the school they dream of being outside the zoning of residence. The limited quota for each school is only receive 5% according to the Permendikbud to new students. Achievement should also be prioritized as a driver and motivate the interest of new students. Classification of achievement participants is carried out. Where is the dataset of prospective students at school before becoming prospective participants for the next school level, as a reference for increasing track quotas achievement.Trying out the Random Tree and Random Forest methods with the Gini Index Algorithm , testing using cross validation as the initial classification model, the dataset is divided into a test and training ratio of 70: 30 then test and analysis to the Random Tree and Random Forest methods with the Gini Index Algorithm , obtained the results of an accuracy of 9 4.39% and using Random Tree with 93.48% accuracy results. But the need for further studies by utilizing more datasets and attributes and comparing to other methods because the test was carried out with 305 datasets, there were 5 attributes and 1 main attribute.