Pengenalan Pola Glyph Lontara Bugis Menggunakan Metode Perceptron Multilayer
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Indrayati, Karunia
Haris, Abdul
Rusjdi, Darma
Haris, Abdul
Rusjdi, Darma
Subject
Teknik Informatika
Datestamp
2022-09-20 02:24:56
Abstract :
Glyph Lontara Bugis contained in old documents have a quality of writing that has a lot of noise because the age of the document is old, therefore the research is done to perform the introduction of glyphs on the sourced from Old documents. This document will be processed by image processing to improve image quality using the image morphology process. The result of the image processing process will be carried out by using the Perceptron Multilayer (PML) method. The result of the process of identifying a Lontara character with the method of Perceptron multilayer This is an application that can recognize the image of Lontara Bugis glyph with the output of readings from glyph image. Then it will be tested validation accuracy validation by comparing data system results using multilayer perceptron algorithm with actual data result or by test using MAPE (Mean Absolute Percentage Error). The results found are the accuracy value using the multilayer perceptron algorithm of 51.001% and an error value of 49.999%.
Glyph Lontara Bugis contained in old documents have a quality of writing that has a lot of noise because the age of the document is old, therefore the research is done to perform the introduction of glyphs on the sourced from Old documents. This document will be processed by image processing to improve image quality using the image morphology process. The result of the image processing process will be carried out by using the Perceptron Multilayer (PML) method. The result of the process of identifying a Lontara character with the method of Perceptron multilayer This is an application that can recognize the image of Lontara Bugis glyph with the output of readings from glyph image. Then it will be tested validation accuracy validation by comparing data system results using multilayer perceptron algorithm with actual data result or by test using MAPE (Mean Absolute Percentage Error). The results found are the accuracy value using the multilayer perceptron algorithm of 51.001% and an error value of 49.999%.
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