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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika dan Teknik Elektro Terapan JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System IKRA-ITH Informatika : Jurnal Komputer dan Informatika IKRA-ITH Teknologi Jurnal Sains dan Teknologi Jurnal Teknoinfo Jurnal Ilmiah Media Sisfo IKRA-ITH ABDIMAS Jurnal Telematika JURTEKSI Jurnal Riset Informatika Zonasi: Jurnal Sistem Informasi JIKA (Jurnal Informatika) Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Teknomatika (Jurnal Teknologi dan Informatika) Jurnal Inovasi Informatika Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Jurnal Ilmiah Wahana Pendidikan Jurnal Media Informatika Jurnal PkM (Pengabdian kepada Masyarakat) TIERS Information Technology Journal Prosiding Konferensi Nasional PKM-CSR Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Dirgamaya: Jurnal Manajemen dan Sistem Informasi Joutica : Journal of Informatic Unisla Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Nasional Teknologi Komputer Jurnal Sistem Informasi dan Teknologi (SINTEK) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Moneter : Jurnal Keuangan dan Perbankan COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Informasi interaktif : jurnal informatika dan teknologi informasi Prosiding SeNTIK STI&K Sintek Kuwera Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Komtika (Komputasi dan Informatika)
Atmojo, Wahyu Tisno
Universitas Pradita
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Journal : Jurnal Riset Informatika

 1 
CLASSIFICATION OF VEHICLE TYPES USING BACKPROPAGATION NEURAL NETWORKS WITH METRIC AND ECENTRICITY PARAMETERS Hendra Mayatopani; Rohmat Indra Borman; Wahyu Tisno Atmojo; Arisantoso Arisantoso
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (730.169 KB) | DOI: 10.34288/jri.v4i1.293

Abstract

One of the efforts to break down traffic jams is to establish special lanes that can be passed by two, four or more wheeled vehicles. By being able to recognize the type of vehicle can reduce congestion. Citran based vehicle classification helps in providing information about the vehicle type. This study aims to classify the type of vehicle using a backpropagation neural network algorithm. The vehicle image can be recognized based on its shape, then the backpropagation neural network algorithm will be supported by metric and eccentricity parameters to perform feature extraction. Then from the results of feature extraction with metric parameters and eccentricity, the object will be classified using a backpropagation neural network algorithm. The test results show an accuracy of 87.5%. This shows the algorithm can perform classification well.
CLASSIFICATION OF VEHICLE TYPES USING BACKPROPAGATION NEURAL NETWORKS WITH METRIC AND ECCENTRICITY PARAMETERS Hendra Mayatopani; Rohmat Indra Borman; Wahyu Tisno Atmojo; Arisantoso Arisantoso
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.834 KB) | DOI: 10.34288/jri.v4i1.139

Abstract

One of the efforts to break down traffic jams is to establish special lanes that can be passed by two, four, or more wheeled vehicles. By being able to recognize the type of vehicle can reduce congestion. Citran based vehicle classification helps in providing information about the vehicle type. This study aims to classify the type of vehicle using a backpropagation neural network algorithm. The vehicle image can be recognized based on its shape, then the backpropagation neural network algorithm will be supported by metric and eccentricity parameters to perform feature extraction. Then from the results of feature extraction with metric parameters and eccentricity, the object will be classified using a backpropagation neural network algorithm. The test results show an accuracy of 87.5%. This shows the algorithm can perform classification well.
Co-Authors Aditya Bima Adrielvino, Nathanael Abel Agus Dendi Rachmatsyah Alfa Yohannis Andi Guna Andi Guna Andreas Indra Wardana Andrew Lowell Aprikasari, Manda Aprikasari, Manda Arisantoso Arisantoso Ayunda, Afifah Trista Belsana Butar Butar Benedicta, Laurence Butar Butar, Belsana Caesar Gracia Chandra, Frans Kenny Christopher Christopher Cynthia, Dessy Nia Cynthia, Maulidania Mediawati Darmawan, Umar Dazki, Erick Deasy Olivia Deasy Olivia Dermawan, Steven Destriana, Rachmat Dewi Monica Didik Setiyadi Dodi Aprilianto Dwi Nisfatul Hijjah Edison Siregar Eka Pandu Cynthia, Eka Pandu Endang Retnoningsih Erika Kristina Ernando, Ryan Felix Felix Feri Prasetyo Feri Prasetyo Halim, Onky Ardhana Hasna Tania Yasmine Heriyando, Damien Hugo Hisyam, Ahmad Abdilah hizkia imanuel Jonathan Juan Antoni Samuel Posumah Kelly Kirsten Audrey Kirsten Audrey, Kelly Kurniawan, Ericka Kesya Masriah Masriah - Masriah Masriah masriah masriah, masriah Master Edison Master Edison Master Edison Siregar Mayatopani, Hendra Muhadi Hariyanto Muhamad Filman Ghaida Firdaus Muhamad Irvansyah Muhammad Haikal Nadda Akilka Ulima Nurhajanti Muljadi Nadda Akilka Ulima Nurhajanti Muljadi Natanael Iwan Santosa Nazwa Wanda Tazkiya Niklas, Hubert Nofry Thrusmida Ocktavia, Shabila Ocktavia, Shabila Oki Sumistriani Panduwitama, Aldira Posumah, Juan Qonita Azizah Qonita Azizah Rachmatsyah, Agus Dendi Rahmawati, Lailia Richardo, Albert Rido Dwi Kurniawan Rohmat Indra Borman Shella Cintiya Stevan Amadeo Prasetyo Susiana Tarisa Mareti, Gusti Teh Yu Ka Untoro, Elianna Katherine Valencia, Shanty Waris Widekso Waris Widekso Wellson, Matthew George Zaenab Islami