System Monitoring Traffic Density Application based on Neural Network Algorithms
The increase in vehicle traffic density in a city correlates with increasing private vehicle usage. This problem is caused by the lack of public transport services. In other side, the volume of private vehicles increases the traffic density and because problems are jammed in rush hour traffic. Use of the application can help road users to know the traffic conditions at real time. The research has developed a mobile application of information about traffic condition. This application is created using Android software programming, Android Development Tool (ADT) integrated with Google Maps so it can display information points from jammed location. The information presented in the form of the location name, location coordinates (latitude, longitude), the average vehicle speed (Km / h) which pass through the area and the traffic status in the form of a solid, jammed or smoothly. The data was predicted by Backpropagation Neural Network. The performance has seen on the size of MSE (Mean Square Error). The result is the smallest MSE are 8,91x10-24, it means the chosen method has a predictability that is very close to the actual conditions of traffic situation
https://www.liputan6.com/bisnis/read/2465078/10-kota-dengan-lalu-lintas-terburuk-di-dunia (diakses 20 Juli 2018)
https://urbandigital.id/aplikasi-lokasi-macet-jalan/(diakses pada tanggal 20 juli 2013)
Mihaela Cardei, Iana Zankina, Ionut Cardei, dan Daniel Raviv, â€œCampus Assistant Application on an Android Platformâ€, Department of Computer and Electrical Engineering and Computer Science Florida Atlantic University.
Peraturan Menteri Perhubungan Nomor: KM 14 Tahun 2006 Tentang Manajemen dan Rekayasa Lalu Lintas di Jalan, 2006
Yi-Chung Hu dan Fang-Mei Tseng, â€œApplying Backpropagation Neural Networks to Bankruptcy Predictionâ€, International Journal of Electronic Bussiness Management, Vol.3, No. 2, pp. 97-103, 2005
Imam Shabri, Mike Yuliana dan Zaqiatul Darojah, â€œPrediksi Penggunaan Bandwidth PENS-ITS menggunakan Jaringan Syaraf Tiruan dengan Algoritma Backpropagationâ€, Jurnal Proyek Akhir Politeknik Elektronika Negeri Surabaya, 2012.
Sri Redjeki, â€œAnalisis Fungsi Aktivasi Sigmoid Algoritma Backpropagation Pada Prediksi Dataâ€, Jurnal Thesis Universitas Gadjah Mada, 2005.
Didi Supriyadi, â€œSistem Informasi Penyebaran Penyakit Demam Berdarah Menggunakan Metode Jaringan Syaraf Tiruan Backpropagationâ€, Thesis Universitas Diponegoro Semarang, 2012.
Daniel Soudry, Itay Hubara dan Ron Meir, â€œExpectation Backpropagation: Parameter-Free Training Of Multilayer Neural Networks With Continuous Or Discrete Weightsâ€, Department of Statistics, Columbia University, 2014.
How to Cite
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.