Penerapan Jaringan Saraf Tiruan Backprogation Dalam Memprediksi Jumlah Pasien Rumah Sakit


Authors

  • Dea Dwi Rizki Tampubolon STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Irfan Sudahri Damanik STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Harly Okprana STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

Keywords:

Artificial Neural Networks; Backpropagation; Prediction,; Hospital Patients

Abstract

Artificial Neural Network is one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. Artificial Neural Network (ANN) is defined as an information processing system that has characteristics similar to human neural networks. ANN is an information processing system that has similar characteristics to a biological neural network. The hospital is an integral part of a social and health organization with the function of providing services, healing disease and preventing disease to the community. Backpropagation network is one of the algorithms that are often used in solving problems. complicated problem. This algorithm is also used in regulatory applications because the training process is based on a simple relationship. The problems that occur at the Djasemen Saragih Pematangsiantar Hospital are the lack of doctors working at the hospital so that there is a density of patients that occur every year, and the absence of patient rooms that are placed at home. ill when there was an increase that was not recognized by the hospital. With the data available every year, it is expected that the use of artificial neural networks using the backprogation method is very useful for the hospital in determining the prediction of the number of hospital patients for the next year can be used as the basic material for changes or additional patient rooms when there is an excess of predicted patients.

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Submitted: 2021-12-23
Published: 2021-12-31
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