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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) CESS (Journal of Computer Engineering, System and Science) Jurnal Inspiration JOIV : International Journal on Informatics Visualization Creative Information Technology Journal SISFOTENIKA Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Komtika (Komputasi dan Informatika) RESEARCH : Computer, Information System & Technology Management DoubleClick : Journal of Computer and Information Technology JurTI (JURNAL TEKNOLOGI INFORMASI) Voice Of Informatics Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Multitek Indonesia : Jurnal Ilmiah JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Ilmiah Sinus Informasi Interaktif Majalah Ilmiah Bahari Jogja CCIT (Creative Communication and Innovative Technology) Journal TAFAQQUH: Jurnal Hukum Ekonomi Syariah Dan Ahwal Syahsiyah Infotekmesin Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Respati Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia JNANALOKA Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Journal of Technology and Informatics (JoTI) SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Ekonomi dan Teknik Informatika Literasi Nusantara Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Techno Innovative: Journal Of Social Science Research Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Teknomatika: Jurnal Informatika dan Komputer Tafaqquh : Jurnal Hukum Ekonomi Syariah dan Ahwal Syahsiyah Explore Jurnal Teknologi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika) Jurnal Bisnis Digital dan Sistem Informasi Jurnal Perangkat Lunak
Hanif Al Fatta
Universitas Amikom Yogyakarta
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Journal : techno

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Image Similarity Searching Use Multi Part Cutting And Grayscale Color Histogram Sofyan Pariyasto; Kusrini Kusrini; Hanif Al Fatta
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 20, No 1 (2019): Techno Volume 20 No.1 April 2019
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v20i1.3817

Abstract

The use of information technology in everyday life continues to increase so rapidly. This is inseparable from the role of researchers, especially in the field of information technology. Information technology has become a necessity so that it is widely used in the fields of education, trade, livestock and even to the agricultural sector. One of the obstacles that is needed is to check all activities involving information systems, especially when there is data in the form of images. Problems that arise are usually needed by humans to check and sort items that have been carried out by humans. This is the background of this research to help reduce activities involving humans. The process of finding the similarity of images in computer vision can be used in several fields such as education, retail, and other fields. In the field of computer vision education can be utilized for the automatic absence process through face recognition, in terms of retailing, it can be used for sorting through object detection. The process of finding similarities between images that are queries and dataset images will be the subject of research, and the process of calculating similarities between queries and datasets will be discussed step by step. The method used in the search process is by calculating the shortest distance between query images and dataset. The steps taken are the extraction feature and then RGB to gray color conversion. The next stage is to cut the image into four parts which will then be calculated the distance of the ecludian. The final part will calculate the performance of the algorithm using the matrix confusion method, so that the test results are in the form of error rates, precision, and accuracy. The trial process uses 30 data using 1000 datasets. In the test results obtained information in the form of recall of 1, 0.66 accuracy and 0.66precision.Keywords: Image Similarity, Histogram Image Grayscale, Ecludiance Distance.
Searching Similarity Digital Image Using Color Histogram Wahyu Wijaya Widiyanto; Kusrini Kusrini; Hanif Al Fatta
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 20, No 1 (2019): Techno Volume 20 No.1 April 2019
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v20i1.3818

Abstract

In the era of globalization and modernization, as now, information technology is widely used in the fields of education, trade, animal husbandry, agriculture and even to the legal sector. One branch of science in the field of information technology that is growing rapidly is computer vision. One of the important roles of computer vision in everyday life is the use of computer vision. This can be applied in terms of face recognition, object detection, and can be applied to group images based on the order of similarity of the image, the ability of computer vision is applied to facilitate human work in selecting from several images to find the most similar images. In this study described the process of finding the similarity of an image with other images through several stages of research flow, the method used is to use RGB values that have been converted to grayscale, then the eucludian distance distance is calculated to determine the value of proximity of an image while calculating performance accuracy algorithm using confusion matrix. The search trial process resulted in an accuracy rate of 0.42, precision of 0.42 and recall 1 of 1000 datasets and 30 random data were taken. Found images that differ in color and shape but when converted into histograms the data has a fairly high similarity to the query. The disadvantage of this research is that images that have histograms similar to queries are displayed as similar images even though the reality is that images are very different from colors and shapes.Keywords: computer vision, similiarity, eucludian distance, grayscale, histogram
Co-Authors AA Sudharmawan, AA Aam Shodiqul Munir Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Agam Saka Jati Agus Susilo Nugroho Agustin, Tinuk Ahmad Hajar Akhmad Dahlan Alvhinia Meinda Amitaba Anas, Syukron Andi Sunyoto Anggie Ariawan Dewa Putra Anggit Dwi Hartanto Anggraini, Resti Kusuma Annas Al Amin Arief Setyanto Arief Tri Nugroho Arvian Sofyan Majid Bambang Soedijono Bambang Soedijono W A Bambang Soedijono, Bambang Barnea, Samson Barnea, Samson Bayu Setiaji Bety Wulan Sari Chan Uswatun Khasanah Chriscel Novian Christian Budi Andrianto, Christian Budi Constantin Menteng Darmanto, Darmanto Dewa Saksana, Jidan Dhana Aulia Ayu Kurniawan Dimas Setiawan Dody Pradipta Donni Prabowo Dwi Sari Widyowaty Ema Utami Eri Sasmita Susanto Faisal Reza Pradhana Fajar Dwi Insani Fandli Supandi Fatimah Nur Arifah Fauji Maulana Ramlan, Fauji Maulana Firstyani Imannisa Rahma Fitriana, Frizka Gori, Takhamo Hadi Sucipto Hafidh Rezha Maulana Hari Agung Budi Santoso Hasan, Nur Fitrianingsih Hendra Kurniawan HENDRA SETIAWAN Hery Maryanto Hidayat Hidayat I Gede Ngurah Arya Indrayasa I Gede Ngurah Arya Indrayasa I Gede Ngurah Arya Indrayasa Imam Adi Nata Khairullah Khairullah Kristama, El Johan Kurniasari, Iin Kusrini Kusrini, K LILIS DWI FARIDA M Suyanto M Suyanto M Suyanto M. Imam Budi Laksamana M. Imam Budi Laksamana M. Nuraminudin M. Suyanto M. Suyanto M. Suyanto M. Suyanto, M. Maksom, Zulisman Moch Ali Machmudi Moh Taufik H Mohammad Suyanto Muhammad Resa Arif Yudianto Muhammad Surahmanto Mutiara Dwi Anggraini NABILA OPER Noor Abdul Haris Noto Narwanto Nugroho Setio Wibowo Nugroho, Rakhmat Prasetyo Agung Nur Khasan Nurmasani, Atik Olivia Maria Inacio Tavares Pamungkas, Prima Giri Purwidiantoro, Moch. Hari Purwoko, Agus Raditya Maulana Anuraga Rahman, Aulia Tegar Rakhma Shafrida Kurnia Risa Helilintar Riska Dwi Handayani Rizki Mawan Safagi, Ardian Yuligar Saifudin, Saifudin Saputra, Artha Gilang Saputra, Artha Gilang Setia Wardani Setiawan, Hendi Siti Rihastuti Sofyan Pariyasto Sri Lestari Rahayu SRI SUMARLINDA Sugihandono, Agus Sutanto, Yudi Suyanto, M Suyanto, M Tigus Juni Betri Tika Dedy Prastyo Tri Nugroho, Arief Tukan, Ewaldus Ambrosius Turah Suhono Tutik Maryana Utama, Hastari Wahyu Sindu Prasetya Widiyanto, Wahyu Wijaya Widyadara , Made Ayu Dusea Wijaya, Tri Amri Wing Wahyu Winarno Wira Dimuksa Wiwi Widayani Yetman Erwadi Yoga Pristyanto Yulia Rahmi Yuliana Yuliana Yusuf Fadlila Rachman Zakaria, Mohd Hafiz Zul Hisyam