Penerapan Jaringan Syaraf Tiruan Deteksi Bahaya Kelebihan Mengkomsumsi Kafein dengan Menggunakan Metode Backpropagation


  • Lidia Sinurat * Mail Budi Darma, Indonesia
  • (*) Corresponding Author
Keywords: Artificial Neural Networks; Backpropagation; Caffeine; Alkaloids

Abstract

Artificial Neural Network (ANN) is one of the artificial representations of the human brain that always tries to simulate the learning process of the human brain. Backpropagation training algorithm or can be translated into back propagation, first formulated by Werbos and popularized by Rumelhart and McCelland to be used in ANN, and then this algorithm is usually appointed as BP. This algorithm includes a supervised training method and design for operations on multi-layer feed forward networks. Caffeine is an alkaloid found in various types of plants, especially coffee plants, colas, tea and so forth. Caffeine functions as a stimulant for the central nervous system, aphrodisiacs and can ward off katuk and restore alertness. But the side effects, caffeine has the potential to cause mutations of chromosomes that are mutagenic

Downloads

Download data is not yet available.

References

Pemograman Matlab pada Sistem Pakar Fuzzy (Mohammad Yazdi Pusadan) 2015

Jong Jek Siang, 2004, Penggunaan Matriks Matlab, Yogyakarta, Penerbit Andi.

Ruth Chrestanti, 2002, Jaringan Saraf Tiruan.

Diyah Puspitaningrum. Pengantar Jaringan Saraf Tiruan Penerbit Andi

Jogiyanto H.M., 1989, Analisis dan Disain, Penerbit Andi.

Badul Anwar, 2011, Algoritma Backpropagation.


Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Penerapan Jaringan Syaraf Tiruan Deteksi Bahaya Kelebihan Mengkomsumsi Kafein dengan Menggunakan Metode Backpropagation

Dimensions Badge
Article History
Submitted: 2020-03-31
Published: 2020-04-30
Abstract View: 503 times
PDF Download: 720 times
How to Cite
Sinurat, L. (2020). Penerapan Jaringan Syaraf Tiruan Deteksi Bahaya Kelebihan Mengkomsumsi Kafein dengan Menggunakan Metode Backpropagation. Journal of Information System Research (JOSH), 1(3), 115-122. Retrieved from https://ejurnal.seminar-id.com/index.php/josh/article/view/126
Issue
Section
Articles