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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) IJISTECH RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Bulletin of Computer Science Research Journal of Social Responsibility Projects by Higher Education Forum BEES: Bulletin of Electrical and Electronics Engineering Jurnal ABDIMAS Budi Darma Bulletin of Multi-Disciplinary Science and Applied Technology
Fince Tinus Waruwu
UNIVERSITAS BUDI DARMA
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Journal : JURTEKSI

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DETECT THE SIMILARITY OF DIGITAL IMAGES USING THE EIGENFACE METHOD Alwin Fau; Fince Tinus Waruwu
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 7, No 2 (2021): April 2021
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v7i2.962

Abstract

Abstract: In today's technological developments, digital images are a medium that is often used to store a person's identity. Digital images are currently widely used for data security needs. On the other hand, images can also be used as a medium for tapping data. Today's digital media provide many things in manipulating and changing the information contained in these images. In this study, the authors conducted a study to examine similarities in digital images so that it could be seen whether the information was authentic or not. detecting image similarities can help find out information whether the image is the same as the original object or not. The method used in this research is the Eigen Face method. The face eigen method is a method that can be used to check and match the similarities of an image. With the eigenface value, Figure 1, Figure 2, Figure 3, it can be determined that with other eigenface values can be determined based on the eigenface matrix values obtained from each image. Based on the values obtained from Figures 1, 2, and 3, it can be concluded that the eigenface method is able to present facial similarities with a presentation value of 80%.            Keywords: Eigenface; Face Recognation; Images; Images Processing  Abstrak: Dalam perkembangan teknologi saat ini, gambar digital merupakan media yang sering digunakan untuk menyimpan identitas seseorang. Gambar digital saat ini banyak digunakan untuk kebutuhan keamanan data. di sisi lain, gambar juga dapat digunakan sebagai media penyadapan data. Media digital saat ini menyediakan banyak hal dalam memanipulasi dan mengubah informasi yang terdapat pada gambar tersebut. Dalam penelitian ini penulis melakukan penelitian untuk menelaah kemiripan pada citra digital sehingga dapat diketahui apakah informasi tersebut otentik atau tidak. Mendeteksi kemiripan citra dapat membantu mengetahui informasi apakah citra tersebut sama dengan objek aslinya atau tidak. Metode yang digunakan dalam penelitian ini adalah metode Eigen Face. Metode eigen wajah merupakan metode yang dapat digunakan untuk mengecek dan mencocokkan kemiripan suatu citra. Dengan nilai eigenface, Gambar 1, Gambar 2, Gambar 3, dapat ditentukan bahwa dengan nilai eigenface lainnya dapat ditentukan berdasarkan nilai matriks eigenface yang diperoleh dari masing-masing citra. Berdasarkan nilai yang diperoleh dari Gambar 1, 2, dan 3, dapat disimpulkan bahwa metode eigenface mampu menghadirkan kemiripan wajah dengan nilai presentasi 80%.. Kata kunci: Citra; Eigenface; Pengolahan Citra Digital; Pengenalan Wajah
Co-Authors Adelina, Putri Dani Adelina, Putri Dani Alwin Fau Anda Yanny Armansyah Ritonga Azlan Azlan Bister Purba Cici Oktaviani Dhea Ulfi Aulia Efori Buulolo Ginting, Permanan Guidio Leonarde Ginting Harahap, Arahman Hotmoko Tumanggor Ilhamsyah Ilhamsyah Imam Saputra Joni Alpensius Simatupang Kamalia Safitri, Kamalia Kevin Maulana Putra Khairunnisa Khairunnisa Lastri Manik Lince Tomoria Sianturi Maringan Sianturi Mayadi Mayadi Mesran, Mesran Muhammad Syahrizal Natalia Silalahi Ndruru, Eferoni Nelly Astuti Hasibuan Niken Aprilia Noveriang Ndruru Panjaitan, Melda Panjaitan, Melda Pratiwi, Wika Elsa Putri Ramadhani, Putri R Wisnu Prio Pamungkas Ramadhan, Puji S Ramadhan, Puji S Ramadhan, Saidi Ramadina Pertiwi Ratih Anggraini, Ratih Rivalri Kristianto Hondro Rivalry Kristianto Hondro Robiah Al-Adawiyah Saidi Ramadan Siregar Santho Baido Hasian Manullang Saragih, Hosianna Sarwandi Wandi Shakya Suci Kamara Siagian, Edward Robinson Sianipar, Sri Handayani Sinambela, Zulhan Sentoso Sindy Nastiti Sri Handayani Sianipar Sri Wulan Sri Wulan, Sri Suginam Surya Darma Nasution Swandi Dedi Arnold Pardede Vify Ernanda Wika Elsa Pratiwi Zai, Evi Safyan Sari