Analysis of Using Binary and Bipolar Data in Knowing the Logic Gate Using Perceptron Method
J Simangunsong1, S Efendi2, P H Putra3
1J Simangunsong, Student, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
2S Efendi, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
3P H Putra, Student, Department of Information Technology, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Indonesia.
Manuscript received on 09 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 1362-1364 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F12370476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Is a logic gate circuit tha forms the basis of the computer. Millions of transistors in a microprocessor forming thousands of logic gates. Some methods or models are frequently used to recognize the logic gate is a method perceptron. Perceptron is a fast and reliable network for a class of problems that can be solved. While the propagation is one of the Artificial Neural Network architecture that has a learning process forward and backward error correction. In this study, the authors analyze the use of binary data and recognizing bipolar logic gate using perceptron. From the results of this study concluded, among others: Methods perceptron can recognize the logic gate much faster than other methods. Binary better use of the bipolar numbers, as the binary number can recognize the logic gate much faster than bipolar numbers. OR and NOR logic gates with binary input and output more quickly recognized than other logic gates with a maximum error of 0.1 and the number of iterations 20.
Keywords: Binary, Bipolar, Logical Gates, Perceptron.
Scope of the Article: Data Analytics