Classification of Bidikmisi Scholarship Acceptance using Neural Network Based on Hybrid Method of Genetic Algorithm

Authors

  • N Cahyani Department of Statistics, Universitas Nahdlatul Ulama Sunan Giri, Bojonegoro, Indonesia
  • Sinta Septi Pangastuti Department of Statistics, Universitas Padjadjaran, Sumedang, Indonesia
  • K Fithriasari Department of Statistics, Institut Teknologi Sepuluh November, Indonesia
  • Irhamah Department of Statistics, Institut Teknologi Sepuluh November, Indonesia
  • N Iriawan Department of Statistics, Institut Teknologi Sepuluh November, Indonesia

DOI:

https://doi.org/10.29244/ijsa.v5i2p396-404

Keywords:

bidikmisi scholarship, genetic algorithm, neural network

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.

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References

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Published

2021-06-30

How to Cite

Cahyani, N., Pangastuti, S. S., Fithriasari, K., Irhamah, I., & Iriawan, N. (2021). Classification of Bidikmisi Scholarship Acceptance using Neural Network Based on Hybrid Method of Genetic Algorithm. Indonesian Journal of Statistics and Its Applications, 5(2), 396–404. https://doi.org/10.29244/ijsa.v5i2p396-404

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