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All Journal Jurnal Sistem Informasi Kaputama (JSIK)
M. Zulhamdany Bangun
STMIK KAPUTAMA
Computer Science & IT

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JARINGAN SYARAF TIRUAN MEMPREDIKSI KEBUTUHAN OBAT-OBATAN MENGGUNAKAN METODE BACKPROPAGATION M. Zulhamdany Bangun; Novryenni Novryenni; Hermansyah Sembiring
JSIK (Jurnal Sistem Informasi Kaputama) Vol 5, No 1 (2021): Volume 5, Nomor 1 Januari 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jsik.v5i1.454

Abstract

Health development is directed at increasing awareness, willingness and ability to live for everyone so that the highest public health status can be realized. In the current era of regional autonomy where health development is the responsibility of the regional government, the regions must be able to regulate themselves, one of which is in fulfilling their drug needs. To fulfill the need for medicine, good processing and planning are needed. One of the facilities or facilities needed for optimal health services to the community is the need for support in the form of drug availability for basic health services to suit their needs. Backpropagation is a multilayer Artificial Neural Network training because the backpropagation method has three layers in the training process, namely the input layer, hidden layer and output layer, where backpropagation is the development of a single layer network (Single Screen Network) which has two layers, namely the input layer and output layer. The drug data used were 2010 to 2019. With a maximum epoch of 0-10000, learning rate 0.1 and target errors ranging from 0.01 to 0.003 to produce convergent results. The results of the prediction of the number of drugs after carrying out the training process and testing have increased and decreased.
Co-Authors Hermansyah Sembiring Novryenni Novryenni