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All Journal TEKNIK INFORMATIKA PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal sistem informasi, Teknologi informasi dan komputer E-Dimas: Jurnal Pengabdian kepada Masyarakat Format : Jurnal Imiah Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah FIFO Jurnal Sisfokom (Sistem Informasi dan Komputer) Kilat JURIKOM (Jurnal Riset Komputer) IJISCS (International Journal Of Information System and Computer Science) JSAI (Journal Scientific and Applied Informatics) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Madani : Jurnal Pengabdian Kepada Masyarakat JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Journal Collabits IJISCS (International Journal of Information System and Computer Science)
Salamah, Umniy
Universitas Mercu Buana
Aerospace Engineering 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mathematics Social Sciences

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Journal : JURIKOM (Jurnal Riset Komputer)

 1 
Prediksi Perambatan Arus Lalu Lintas Berdasarkan Korelasi Tertinggi Antar Jalan Bagus Priambodo; Yuwan Jumaryadi; Umniy Salamah
JURIKOM (Jurnal Riset Komputer) Vol 9, No 3 (2022): Juni 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i3.4203

Abstract

Over the past few years, many algorithms for traffic flow predictions have been proposed to predict traffic flow. Time series models and neural network models have been widely implemented to predict traffic flow and traffic congestion based on traffic data, vehicle speed, weather, accidents, and special days. However, most of previous studies are used to predict traffic flow, not applied to predict the propagation of traffic flow. Traffic flow propagation is an interesting study. Using this finding the driver can avoid neighboring roads affected by road congestion. We propose the correlation method to find the relationship between the road. To evaluate the relationship between the road, we display the correlation results in the map. The visualization show that the correlation of traffic when congestion occurs shows better in showing the relationship between the road than the correlation at all times
Co-Authors Ahmad Ali Mutezar Aldi Rahman Andi Nugroho, Andi Andi Purnomo Andrean, Rifky Anita Ratnasari Anjar Hero Wilarto Arey Nur Warisman Arrachman, Abdul Kholiq Athillah, Naufal Ayumi, Vina Bagus Priambodo Bagus Priambodo Bagus Priambodo Bagus Priambodo Chairulsyah, Diofavian Rafif Desi Ramayanti Dheo Alpian Nanda Krisna Dianing Asri, Sri Eka Maulana Fajriah, Riri Fajrin Nur Utami Fani Putri Oktavia Fauzi Nur Iman Gusty Age Rusandy Handrie Noprisson Ida Farida Ida Farida Inge Handriani, Inge Irene Ananda Iryani, Lemi Ivan Hardi Pratama Jumaryadi, Yuwan Kurnia Kito, Ramadani Lystha, Arie Maritza, Kaka Irsyad Noprisson, Handrie Nur Iman, Fauzi Panggabean, Claudio Nehemia Prasha, Achmad Ardani Purba, Mariana Putra, Erwin Dwika Richi Ramadhan Sambada, Arga Sarwati Rahayu Sarwati Rahayu Sarwati Rahayu Setiawan, Hadiguna Soemantri, Syauqi Adli Sulis Sandiwarno, Sulis Suratno, Igo Prayoga Syifa Fauziah Vera Yunita Vina Ayumi Vincentius Krisna Aditya Warisman, Arey Nur Wibowo, Aditya Dwi Zamzami, Muhammad Aryaka