Prediction of Main Transportation Modes using Passive Mobile Positioning Data(Passive MPD)

Prediction of Main Transportation Modes using Passive Mobile Positioning Data(Passive MPD)

prediction; Active MPD; Passive MPD; main transportationmode

Indicators of the main mode of transportation used by domestic touristsduring tourism trips cannot yet be estimated using Passive MPD which is recorded based on the location of the BTS that captures the cellular activity ofdomestictourists. Previous research on identifying transportation modes from Passive MPD has its ownshortcomings because it only relies on speed and travel time features. Meanwhile, there is Active MPD which is recorded using active geo-positioning and real-time, where the research involves many features and has a data structure similar to Passive MPD. Therefore, this research aims to conduct a study of the implementation of the method used to identify modes of transportation in Active MPDs to Passive MPDs as an approachto predicting the main modes of transportation. As a result, the transportation mode identification method in the Active MPD can be implemented in the Passive MPD. The best accuracy of 83.56% was obtained by the LightGBM model using all features. However, the Multinomial Logistic Regression model, which only uses 10 selected features, is the most effective and efficient model with an accuracy of 76.43% and a much shorter execution time.

Muhammad Farhan1,Lya Hulliyyatus Suadaa2*, Sugiri3, AlfatihahReno MNSP Munaf4, Setia Pramana5

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6128/1008

Politeknik Statistika STIS, Jakarta,Indonesia

24-01-2025

FAJAR BAGUS W

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