IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Vol 14, No 2 (2020): April

Traffic Density Classification Using Twitter Data and GPS Based On Android Application

Mohammad Afrizal (Master Program of Computer Science
FMIPA UGM, Yogyakarta)

Idham Ananta Timur (Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta)



Article Info

Publish Date
30 Apr 2020

Abstract

Increasing the number of vehicles in Special Region of Yogyakarta caused by congestion occurred at various traffic points in Special Region of Yogyakarta. The solution to reducing congestion is by increasing the use of public transportation within the city, but it still not in demand by the public. Optimizing daily activities, community always tries to avoid the traffic density on the road to be bypassed.Some research on social media has been used to detect traffic density anomalies. However, the system still cannot provide traffic density information on roads that will be passed by the user because it is just a mapping. Based on this problem, this study aims to classify the traffic density on the road that will be passed by users in the Special Region of Yogyakarta into the category of high traffic and low traffic by utilizing Twitter and GPS data.The results show that Android Applications are able to classify traffic density on the road to be traversed using Geonames.org API. Using the naïve bayes classification algorithm, the system can classify traffic density on 14 streets with an average accuracy of 77.5%, 90% precision, 79.1% recall, and 82.8% f-score.

Copyrights © 2020






Journal Info

Abbrev

ijccs

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so ...