Application of 2DPCA and SOM Algorithms to Identification of Digital Signature Ownership

Abstract

<p class="Isiabstrak"><span lang="EN-US">Signature Is one of the proofs for ratification, one of which is a thesis document, with the development of the when conventional signatures have begin to switch to digital signatures, where digital signatures already have a legal umbrella in Indonesia, currently Covid is still hitting Indonesia, forcing some agencies change the ratification of a document using a digital signature, so that it can provide an opening for falsifying digital signature ratification. Therefore, an application is needed to identify the ownership of a digital signature image, with the first research stage is to collect a digital signature dataset in the form of a signature image or take a dataset from a published legal document, an example of a second stage publication manages the image processing with grayscale first to get extra features and then analyzes the extra feature image using 2DPCA, and identification To get the best matching of image units using the Single Organizing Maps (SOM) method. the results of this study are using the 2DPCA algorithm and SOM to identify ownership of digital signatures, with 84 correct and incorrect test results, from a total dataset of 91 patterns. And get the highest accuracy value of 92.3% at a 20000 translation and a rate of 0.9.</span></p>