ANALISIS ALGORITMA BACKPROPAGATION UNTUK MENGIDENTIFIKASI MAHASISWA YANG DROP OUT DARI KAMPUS

dc.contributor.authorSyahputra, Irfan
dc.date.accessioned2023-05-20
dc.date.available2023-05-20
dc.date.issued2021
dc.identifier.uri https://jurnal.unds.ac.id/index.php/dsi/article/download/13/1
dc.description.abstract Drop-out is a form of failure to follow the students in the educational process at university. The number of students drop out in addition detrimental to the personal / individual, it is also detrimental to higher education institutions themselves. Therefore, it is necessary to study to find the causes or factors that affect student drop-out so it can be useful information for success in higher education. Methods backpropagation artificial neural network is a mathematical model that is used for the identification and classification based training and learning is done. In this study, backpropagation artificial neural network method used in identifying factors - factors causing the drop-out experienced by the students by making learning of the data - the data attributes of students drop out. Backpropagation artificial neural network implementation is done in this study produces good results where backpropagation artificial neural network can produce factors that cause dropouts appropriate to attribute a given student. Keywords: Artificial Intelligence, Artificial Neural Network, Backpropagation, university, High grade student, Drop Out. en_US
dc.language.isoenen_US
dc.publisherUniversitas Harapan Medanen_US
dc.subjectJaringan Saraf Tiruanen_US
dc.titleANALISIS ALGORITMA BACKPROPAGATION UNTUK MENGIDENTIFIKASI MAHASISWA YANG DROP OUT DARI KAMPUSen_US
dc.typeSkripsien_US


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