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Baris 1: [[Berkas:Artificial neural network.svg\|jmpl~~\|300px~~\|Jaringan saraf tiruan merupakan jaringan dari unit pemroses kecil yang saling terhubung, yang dimodelkan berdasar jaringan saraf ([[neuron]]) [[manusia\|jaringan saraf]].]] '''Jaringan saraf tiruan (JST)''' (~~[[Bahasa Inggris]]: ''~~{{lang-en\|artificial neural network}}; (ANN~~)''~~, atau ~~juga disebut~~ ''simulated neural network'' (SNN)'', atau ~~umumnya hanya disebut~~ ''neural network'' (NN)''), adalah [[jaringan]] dari sekelompok unit pemroses kecil yang dimodelkan berdasarkan [[~~Sistem saraf\|~~sistem saraf]] manusia]]. JST merupakan sistem adaptif yang dapat mengubah strukturnya untuk memecahkan masalah berdasarkan informasi eksternal maupun internal yang mengalir melalui jaringan tersebut. Oleh karena sifatnya yang adaptif, JST juga sering disebut dengan jaringan adaptif.<ref>{{Cite journal\|last=Nasution\|first=Darmeli\|last2=Harumy\|first2=T. Henny F.\|last3=Haryanto\|first3=Eko\|last4=Fachrizal\|first4=Ferry\|last5=Julham\|last6=Turnip\|first6=Arjon\|date=2015-10\|year=2015\|title=A classification method for prediction of qualitative properties of multivariate EEG-P300 signals\|url=http://dx.doi.org/10.1109/icacomit.2015.7440180\|journal=2015 International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT)\|publisher=IEEE\|volume=\|issue=\|pages=\|doi=10.1109/icacomit.2015.7440180\|isbn=978-1-4673-7408-8}}</ref> Secara sederhana, JST adalah sebuah alat pemodelan [[data]] [[statistik]] non-linier. JST dapat digunakan untuk memodelkan hubungan yang kompleks antara input dan output untuk menemukan pola-pola pada data. Menurut suatu teorema yang disebut "teorema penaksiran universal", JST dengan minimal sebuah lapis tersembunyi dengan fungsi aktivasi non-linear dapat memodelkan seluruh fungsi terukur Boreal apapun dari suatu dimensi ke dimensi lainnya.<ref> Kurt Hornik, Maxwell Stinchcombe, Halbert White, Multilayer feedforward networks are universal approximators, Neural Networks, Volume 2, Issue 5, 1989, Pages 359-366, ISSN 0893-6080, <nowiki>http://dx.doi.org/10.1016/0893-6080(89)90020-8</nowiki>. (<nowiki>http://www.sciencedirect.com/science/article/pii/0893608089900208</nowiki>) Keywords: Feedforward networks; Universal approximation; Mapping networks; Network representation capability; Stone-Weierstrass Theorem; Squashing functions; Sigma-Pi networks; Back-propagation networks</ref> ~~</ref>~~ == Sejarah == Baris 17 ⟶ 16: == Lihat pula == {{~~wikibooks~~Wikibooks\|Artificial Neural Networks}} ~~<div style="-moz-column-count:2; column-count:2;">~~ * [[20Q]] * [[Artificial life]] Baris 50 ⟶ 48: * [[Systolic automaton]] * [[Time delay neural network]] (TDNN) ~~</div>~~ == Daftar pustaka == ~~<div class="references-small">~~ * {{cite book\|author=Bar-Yam, Yaneer\|title = [http://necsi.org/publications/dcs/Bar-YamChap2.pdf Dynamics of Complex Systems, Chapter 2]\|year = 2003\|}} * {{cite book\|author=Bar-Yam, Yaneer\|title = [http://necsi.org/publications/dcs/Bar-YamChap3.pdf Dynamics of Complex Systems, Chapter 3]\|year = 2003\|}} * {{cite book\|author=Bar-Yam, Yaneer\|title = [http://necsi.org/publications/mtw/ Making Things Work]\|year = 2005\|}} Please see Chapter 3 * Bhagat, P.M. (2005) ''Pattern Recognition in Industry'', Elsevier. ISBN 0-08-044538-1 * Bishop, C.M. (1995) ''Neural Networks for Pattern Recognition'', Oxford: Oxford University Press. ISBN 0-19-853849-9 (hardback) or ISBN 0-19-853864-2 (paperback) * Duda, R.O., Hart, P.E., Stork, D.G. (2001) ''Pattern classification (2nd edition)'', Wiley, ISBN 0-471-05669-3 * Gurney, K. (1997) ''An Introduction to Neural Networks'' London: Routledge. ISBN 1-85728-673-1 (hardback) or ISBN 1-85728-503-4 (paperback) * Haykin, S. (1999) '' Neural Networks: A Comprehensive Foundation'', Prentice Hall, ISBN 0-13-273350-1 * Fahlman, S, Lebiere, C (1991). ''The Cascade-Correlation Learning Architecture'', created for [[National Science Foundation]], Contract Number EET-8716324, and [[Defense Advanced Research Projects Agency]] (DOD), ARPA Order No. 4976 under Contract F33615-87-C-1499. [http://www.cs.iastate.edu/~honavar/fahlman.pdf electronic version] * Hertz, J., Palmer, R.G., Krogh. A.S. (1990) ''Introduction to the theory of neural computation'', Perseus Books. ISBN 0-201-51560-1 * Lawrence, Jeanette (1994) ''Introduction to Neural Networks'', California Scientific Software Press. ISBN 1-883157-00-5 * Masters, Timothy (1994) ''Signal and Image Processing with Neural Networks'', John Wiley & Sons, Inc. ISBN 0-471-04963-8 * Ness, Erik. 2005. [http://www.conbio.org/cip/article61WEB.cfm SPIDA-Web]. ''Conservation in Practice'' 6(1):35-36. On the use of artificial neural networks in species taxonomy. * [[Brian D. Ripley\|Ripley, Brian D]]. (1996) ''Pattern Recognition and Neural Networks'', Cambridge * Smith, Murray (1993) ''Neural Networks for Statistical Modeling'', Van Nostrand Reinhold, ISBN 0-442-01310-8 * Wasserman, Philip (1993) ''Advanced Methods in Neural Computing'', Van Nostrand Reinhold, ISBN 0-442-00461-3 ~~</div>~~ == Referensi == <references /> == Pranala luar == * [http://www.learnartificialneuralnetworks.com/ Selayang pandang Algoritme Jaringan Saraf Tiruan] * [http://dmoz.org/Computers/Artificial_Intelligence/Neural_Networks/ Pranala Open Directory] * [http://www.neurosecurity.com/articles.php Artikel tentang Jaringan Saraf Tiruan]

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