Pengenalan Barcode Pada Identitas Mahasiswa Dengan Menggunakan Metode Learning Vector Quantization

 (*)Oskar Noviandi Nababan Mail (STMIK Kaputama, Binjai, Indonesia)
 Akim Manaor Hara Pardede (STMIK Kaputama, Binjai, Indonesia)
 Rusmin Saragih (STMIK Kaputama, Binjai, Indonesia)

(*) Corresponding Author

Abstract

One of the ways that humans use to uniquely encode some data is barcodes. Encrypted data is usually data relating to information about an item. Items marked with a barcode will facilitate the checkout process. The input devices used to read barcodes require a precise angular position of the barcode in order to be read and we often see barcodes with scratches or sounds that conventional barcode readers cannot recognize. Based on the tests carried out, the ANN-LVQ classification method has a very good level of barcode recognition accuracy, from 100 types of barcodes tested, 96% of normal barcodes and 92% of barcodes can be recognized, codes with less than 20% noise can be recognized.

Keywords


Accuracy, Barcode, Data, Information, Learning Vector Quantization



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References

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Copyright (c) 2022 Oskar Noviandi Nababan, Akim Manaor Hara Pardede, Rusmin Saragih

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