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HILDA AMALIA
Program Studi Manajemen Informatika Akademi Manajemen Informatika dan Komputer Bina Sarana Informatika AMIK BSI JAKARTA
Computer Science & IT

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OPTIMASI NEURAL NETWORK MENGGUNAKAN GENETIC ALGORITHM UNTUK PREDIKSI PENYAKIT DIABETES HILDA AMALIA
Paradigma Vol 17, No 2 (2015): Periode September
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (444.042 KB) | DOI: 10.31294/p.v17i2.751

Abstract

leading to death . People suffering from this disease are unaware that they suffer from diabetes. early detection is required in order to avoid the risk of more severe complications and risk of death. Today many data mining applications are applied to solve problems in the medical world. The ability of data mining is very important that one of them is generating the prediction and classification, the ability to make a prediction and classification makes data mining became popular in the world of health. Results obtained from the processing of data mining can be used as new knowledge to predict adverse health events in the future that can be overcome. In this research will be to improve the accuracy of the method optimization value nerutal network using genetic algorithm optimization method. The value of diabetes dataset processing accuracy by using a neural networkt is 74.46% while the value of accuracy by using a neural network optimization algorithm genetich is 77.10%.
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