Suitability Level Analysis of Google Map’s Travel Time and Traffic Density Classification

https://doi.org/10.22146/jgise.51134

Laksita Amelia Paramesti(1*), Dedi Atunggal(2)

(1) Gadjah Mada University
(2) Gadjah Mada University
(*) Corresponding Author

Abstract


 Traffic congestion is one of problem that occur in big cities, therefore people need traffic information to determine traffic condition. One of many applications that provides traffic information is Google Maps. From the information generated, there are insuitability between google maps’s traffic update and travel time with the actual condition. So the aim of this study is to analyze the suitability level of traffic density classification and google maps travel time. Based on the speed range by Google, the level of suitability can be determined, while the google maps travel time is done by statistical tests. The statistical test used is a statistical test of two parameters using table t with 95% confidence level. The results of this study indicate that the level of suitability of the traffic classification only reaches 35%. The low level of suitability is caused by network latency. While information on google maps travel time does not have a significant difference in actual time.

Keywords


Google maps, E-GNSS, waktu tempuh, estimated time of arrival, kepadatan lalu lintas

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References

Anonim. (2018). Google Maps traffic updates & ETA: How accurate?. Available at: https://www.team-bhp.com/forum/street-experiences/200071-google-maps-traffic-updates-eta-how-accurate.html

Amirian, P., Basiri, A. and Morley, J. (2016) Predictive analytics for enhancing travel time estimation in navigation apps of Apple, Google, and Microsoft. Oxford, UK: Arxiv.org. doi: 10.1145/3003965.3003976.

Burns, C and Sauers,PM. (2014) Google Search Secret. Chicago. American Library Association

Ashish (2016) How Does Google Maps Know About Traffic Condition. Available at: https://www.scienceabc.com/innovation/how-does-google-maps-know-about-traffic-conditions.html.

Chaim, G. (2017) Google Maps Now Can Tell You The Best Time of Day to Travel to Your Destination. Available at: https://www.theverge.com/2017/7/14/15973384/google-maps-update-travel-time-when-to-leave-directions-android.

Mardhiyah, W. (2018) Verifikasi Tingkat Kepadatan Arus Lalu Lintas di Google Maps Pada Beberapa Lampu Apill di Daerah Istimewa Yogyakarta. Yogyakarta: Universitas Gadjah Mada.

Mathew, C. and Simon, M. (2018) How Google Maps Predict Traffic and Knows How Long Your Journey Will Take. Available at: https://www.chroniclelive.co.uk/news/north-east-news/how-google-maps-predicts-traffic-14154099.

Riyanto, S. (2010) Analisis Pengaruh Kecepatan Terhadap Pusat Perbelanjaan. Yogyakarta: Universitas Gadjah Mada.



DOI: https://doi.org/10.22146/jgise.51134

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