Jaringan Saraf Tiruan Pengenalan Pola Karakter Kabataku Menggunakan Metode Bidirectional Associative Memory (BAM) Kontinu
DOI:
https://doi.org/10.30865/jurikom.v9i5.5016Keywords:
Artificial intelligence, Artificial Neural Networks, Pattern Recognition, Continuous BAM, SigmoidAbstract
Artificial neural network is an information processing paradigm with a working system using biological concepts in processing information so that it has capabilities similar to the human brain, Jst is able to solve problems using uncertainty science such as Kabataku pattern recognition. Kabataku is a character operator used in Mathematics with the concepts of X, :, + and -. Introduction This character operator uses the concept of artificial intelligence, which uses the theory and process of Artificial Neural Networks. The purpose of this study is to determine the effectiveness of the Continuous BAM method in recognizing Kabataku character patterns in arithmetic operations in mathematics. The Bidirectional Associative Memory (BAM) method has the ability in associative memory or content addressable memory can be called by using the part stored in the memory itself. BAM in an artificial neural network has 2 layers, namely the input layer and the output layer that are interconnected between the two, also called bidirectional, with the work process if the matrix weight of the signal sent from the input layer X to the output layer Y is W, then the matrix weight of the signal sent from the output layer Y to the input layer X is WT . Continuous BAM method will change the input to output more finely with a value that lies in the range [0,1]. The activation function used is the sigmoid function. The final result of pattern recognition is x1= [-8 -12], x2 =[ 8 0], x3 [12 8], x4= [16 12] Not all patterns match the target.
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