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All Journal Indonesian Journal of Statistics and Its Applications
N Iriawan
Department of Statistics, Institut Teknologi Sepuluh November, Indonesia
Computer Science & IT Mathematics Other

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Classification of Bidikmisi Scholarship Acceptance using Neural Network Based on Hybrid Method of Genetic Algorithm N Cahyani; Sinta Septi Pangastuti; K Fithriasari; Irhamah Irhamah; N Iriawan
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p396-404

Abstract

A Neural network is a series of algorithms that endeavours to recognize underlying relationships in a set of data through processes that mimic the way human brains operate. In the case of classification, this method can provide a fit model through various factors, such as the variety of the optimal number of hidden nodes, the variety of relevant input variables, and the selection of optimal connection weights. One popular method to achieve the optimal selection of connection weights is using a Genetic Algorithm (GA), the basic concept is to iterate over Darwin's evolution. This research presents the Neural Network method with the Backpropagation Neural Network (BPNN) and the combined method of BPNN with GA, where GA is used to initialize and optimize the connection weight of BPNN. Based on accuracy value, the BPNN method combined with GA provides better classification, which is 90.51%, in the case of Bidikmisi Scholarship classification in East Java.
Co-Authors Irhamah - K Fithriasari N Cahyani Sinta Septi Pangastuti