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HILDA AMALIA
Program Studi Manajemen Informatika AMIK BSI Jakarta
Computer Science & IT

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PENERAPAN METODE NEURAL NETWORK BERBASIS PARTICLE SWAM OPTIMIZIED UNTUK PREDIKSI KESUBURAN PADA PRIA HILDA AMALIA
Paradigma Vol 17, No 1 (2015): Periode Maret
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (313.377 KB) | DOI: 10.31294/p.v17i1.738

Abstract

The fertility rate is to be considered, especially for adult men is because infertility is a global problem that occurs in couples. Infertility can result in couples unable to conceive. Infertility in one partner may terminate especially male lineage. Its high level of infertility in today's society can be caused by several things between environmental factors and lifestyle of today's society. Previous research on fertility has been done is by using artificial neural network and produce 82% accuracy. In this paper will be improving the accuracy of neural network method for predicting male fertility through semen using particle swam optimazed (PSO). The survey results revealed that the use of the optimization method can improve the accuracy of the method used in this study was obtained accuracy of new methods for neural network improved its performance using PSO to 92%.
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