Penerapan Metode Klasifikasi Decision Tree Untuk Memprediksi Kelulusan Tepat Waktu
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Jauhar, Ma’sum
Subject
T Technology (General)
Datestamp
2021-11-18 04:53:56
Abstract :
Education is a conscious and planned effort to create learning atmosphere and learning process so that students actively develop their potential. The lack of utilization of stored data makes this data less added value to the institution. Therefore, it is necessary to use these data in order to produce useful knowledge for study programs and universities. IT Telkom Purwokerto has 3 faculties, consist of twelve undergraduate study programs and just one D3 study program. In 2017, the entries path opened by IT Telkom Purwokerto are Mandiri, Kemitraan, and Prestasi. The purpose of this study is to predict student performance in completing the study period on time. The limitation of this research is only in the undergraduate program. The attributes used in this study are clusters of regional origin based of PDRB, study program, registration path, school origin, field of expertise, 2019/2020 odd semester GPA, and graduation status for Final Project 1 and Proposal Seminars. Sources of data in this study are obtained from the New Student Admissions (PMB), Academic Institutions, and SISFO. The method used in this research is the decision tree classification method. This study produced 63 rules with the results are accuracy of 68.49%, precision value of 79.63% and a recall value of 55.13%. Keyword : Data Mining, Classification, PDRB, Decision tree, Graduation
Education is a conscious and planned effort to create learning atmosphere and learning process so that students actively develop their potential. The lack of utilization of stored data makes this data less added value to the institution. Therefore, it is necessary to use these data in order to produce useful knowledge for study programs and universities. IT Telkom Purwokerto has 3 faculties, consist of twelve undergraduate study programs and just one D3 study program. In 2017, the entries path opened by IT Telkom Purwokerto are Mandiri, Kemitraan, and Prestasi. The purpose of this study is to predict student performance in completing the study period on time. The limitation of this research is only in the undergraduate program. The attributes used in this study are clusters of regional origin based of PDRB, study program, registration path, school origin, field of expertise, 2019/2020 odd semester GPA, and graduation status for Final Project 1 and Proposal Seminars. Sources of data in this study are obtained from the New Student Admissions (PMB), Academic Institutions, and SISFO. The method used in this research is the decision tree classification method. This study produced 63 rules with the results are accuracy of 68.49%, precision value of 79.63% and a recall value of 55.13%. Keyword : Data Mining, Classification, PDRB, Decision tree, Graduation
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