مؤسسة الشرق الأوسط للنشر العلمي

عادةً ما يتم الرد في غضون خمس دقائق

الإصدار العاشر: 6 فبراير 2021
من مجلة الشرق الأوسط للنشر العلمي

Predicting Education Dropout in Benghazi City and its suburbs by Using Classification Trees

Osama H. Othman, & Eyman Musa Farag Farag
Abstract

Abstract

The education sector is considered to be one of the most important sectors in any society , it is the corner stone toward the progress and development , therefore ministers of educations, presidents and heads of universities and schools have prepared the education cadres to enable them to participate in building the society. Despite the attention that countries pay toward education, still there is a big problem facing this attention that most countries have failed to solve, it is the dropout of education. In this work our aim is the prediction of the factors (variables) that likely influence education dropout. The utilized statistical model for that purpose is classification trees, which is a nonparametric data mining device that suit our database and meet our aim of the study. The target here is to predict students who will probable dropout the study at secondary school and not proceed their study to universities or high institutes

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