Model Identifikasi Pemalsuan Ijazah menggunakan Gabor Wavelet dan Gaussian Mixture Models Super Vektor (GMM-SV) - Alfina Alfina; Dzulgunar Muhammad Nasir (KITA Institute, 2020)
Various cases occur related to certificate falsification and some people and educational institutions have to deal with the law, this problem is not impossible to abuse along with advances and technological innovation with various tools that can be used by anyone. Identifying the diploma document must be of particular concern to tertiary institutions to minimize the associated fake diplomas and the diploma legalization process. In legalizing the diploma for STMIK Indonesia Banda Aceh students, checking the authenticity of the certificate is only by bringing the original certificate and photocopy of the certificate or by contacting the academic party who issued the certificate, this process is sometimes missed by officers when the queue is crowded. The specific objectives of the research include implementing a model and feature method of Gabor Wavelet and Gaussian Mixture Models Super Vector (GMM-SV) for document identification to speed up diploma identification. The flow of this research starts from the input in the form of a basic image as an image that a reference for the authenticity of the diploma. Then the test image input is an image that will be tested for authenticity. The results showed that using the Gabor Wavelet feature and the Gaussian Mixture Models Super Vector (GMM-SV) could identify fake diplomas with an accuracy rate of 92.8%.