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All Journal Creative Information Technology Journal Journal of Information Technology and Computer Science (JOINTECS) Generation Journal Jurnal ABDINUS : Jurnal Pengabdian Nusantara JAMI: Jurnal Ahli Muda Indonesia Joutica : Journal of Informatic Unisla Nusantara of Engineering (NOE) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Danar Putra Pamungkas
Universitas Nusantara PGRI Kediri
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation

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Journal : Creative Information Technology Journal

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Pengenalan Citra Tanda Tangan Menggunakan Metode 2D-LDA dan Euclidean Distance Danar Putra Pamungkas; Fajar Rohman Hariri
Creative Information Technology Journal Vol 3, No 4 (2016): Agustus - Oktober
Publisher : UNIVERSITAS AMIKOM YOGYAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.272 KB) | DOI: 10.24076/citec.2016v3i4.83

Abstract

Kelemahan sistem manual dalam identifikasi tanda tangan adalah si pemeriksa tanda tangan harus teliti dalam melakukan pencocokan untuk menghindari kesalahan. Oleh karena itu untuk mengatasi kelemahan pencocokan tanda tangan secara manual, proses pencocokan tanda tangan perlu dilakukan secara otomastis dengan sistem komputer sehingga diharapkan mempermudah dalam identifikasi tanda tangan seseorang. Pada penelitian ini peneliti menggunakan metode 2DLDA dan Euclidean Distance untuk pengenalan tanda tangan dengan sistem komputer. Metode 2DLDA untuk ektraksi fitur citra tanda tangan dan metode Euclidean Distance untuk klasifikasi citra tanda tangan. Data citra tanda tangan yang digunakan berukuran 50x50, 100x100, 150x150, 200x200 dan 250x250 piksel. Hasil dari uji coba penelitian ini adalah akurasi pengenalan citra tanda tangan menggunakan metode 2DLDA mencapai 88% dan rata-rata akurasi 81%. Akurasi optimal pengenalan citra tanda tangan dengan metode 2DLDA terjadi pada penggunaan data citra berukuran 50x50 piksel dengan akurasi 88% dan kecepatan 0.20126 detik.The manual system in the identification of the examiner's signature is the signature must be meticulous in doing matching to avoid mistakes. Therefore, to overcome the disadvantages of signature matching manually, signature matching process needs to be done should automatically with a computer system that is expected to facilitate the identification of a person's signature. In this study, researchers used a method 2DLDA and Euclidean Distance to the introduction of a signature with a computer system. 2DLDA methods to extract image features the signature and Euclidean Distance method for image classification signature. The image data signature used measuring 50x50, 100x100, 150x150, 200x200 and 250x250 pixels. The results of this research trial is a signature image recognition accuracy using 2DLDA reaches 88% and an average accuracy of 81%. Optimum accuracy signature image recognition method 2DLDA occurs in the use of image data size of 50x50 pixels with 88% accuracy and speed 0.20126 seconds
Co-Authors Abdul Azis Ahmad Bagus Setiawan Ahmad Minanul Aziz Anis Nur Rohmah Ardhi Mardiyanto Indra Purnomo Danang Wahyu Widodo Daniel - Swanjaya Dwi Fikri Haika Eko Nur Cahyono Fajar Rohman Hariri Firmansyah Mukti Wijaya Ibram Farhani Yusuf Imam Wicaksono Joko Purwanto Laili Rahma Fauziyah M Anas Restuning Pamuji Mohamad Inung Pangestu Nadya Khalisah Zuhal Patmi Kasih Resty Wulaningrum Resty Wulanningrum Saiful Hamzah Tanggon Maulana Mahardika Taufik Rizki Kurniawan Tri Krisna Wati Aprilia Triyo Kristantio Yulingga Nanda Hanief