Bipolar Approach in Recognition of Gorga Batak Patterns with the Hebbian Method
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Abstract
The recognition of shapes or patterns in Intelligent Artificial is a method that is developing very rapidly and is continuously being developed to this day. The need for information contained in a pattern or form is very useful to be developed and applied properly to the health or culture sector, by using a system that is embedded with a capability or feature in pattern recognition. This model can be applied both to face pattern recognition, patterns. Likewise in this discussion about the pattern recognition of the Gorga Batak using artificial neural networks, namely the Hebbian method. With two patterns as knowledge or learning base and then tested. The input pattern will be checked for the similarity of the two learning base patterns, whether it is recognized as the Gorga “Simeol – eol” pattern or as the Gorga “Sitompi” pattern. By using 25 input variables and bias 1 with an initial weight value of 0, the Gorga “Someol-eol” and “Sitompi” patterns were initialized to a grayscale image and then extracted to a bipolar image with values of 1 and -1. The Gorga “Simeol – eol” pattern has a target of 1 and the Gorga “Sitompi” pattern has a target of -1, the function f (net) is 1 if Y > = 0 and -1 if Y < 0. From the process carried out, it is found that the Gorga “Simeol – eol” pattern is obtained the value of Y = 12 and for the Gorga “Sitompi” pattern Y = -12, and inputted to the function f (net), the result is the same as the target 1 for the Gorga “Simeol –eol” pattern and -1 for the Gorga “Sitompi” pattern.
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