Results 1 to 10 of about 15,881 (165)

Travel pattern-based bus trip origin-destination estimation using smart card data. [PDF]

open access: yesPLoS ONE, 2022
Smart card data are widely used in generating the origin and destination (O-D) matrix for public transit, which contains important information for transportation planning and operation.
Inmook Lee   +4 more
doaj   +2 more sources

Exploring Equity in Public Transportation Planning Using Smart Card Data [PDF]

open access: yesSensors, 2021
Existing public transport (PT) planning methods use a trip-based approach, rather than a user-based approach, leading to neglecting equity. In other words, the impacts of regular users—i.e., users with higher trip rates—are overrepresented during ...
Kiarash Ghasemlou   +2 more
doaj   +2 more sources

Smart Card Data Mining of Public Transport Destination: A Literature Review

open access: yesInformation, 2018
Smart card data is increasingly used to investigate passenger behavior and the demand characteristics of public transport. The destination estimation of public transport is one of the major concerns for the implementation of smart card data.
Tian Li   +3 more
doaj   +3 more sources

Pemanfaatan AES dengan Key Dinamis sebagai Metode Pengamanan Data pada Smart Card

open access: yesSistemasi: Jurnal Sistem Informasi, 2021
Abstrak Terjadinya pandemi Covid-19 di hampir seluruh belahan dunia, termasuk Indonesia, menjadikan masyarakat mempunyai gaya hidup baru dalam bertransaksi untuk mencegah penularan virus sesuai anjuran Pemerintah.
Noprianto Noprianto   +2 more
doaj   +1 more source

Efektifitas Media Smart Card (Kartu Pintar) dalam Meningkatkan Hasil Belajar Pembelajaran Tematik

open access: yesDawuh Guru, 2022
Tujuan penelitian ini adalah untuk mengetahui efektivitas media smart card (kartu pintar) pada pembelajaran tematik di MIN 2 Kota Padang. Penelitiannya merupakan lapangan yang bersifat deskriptif kualitatif.
Rendy Nugraha Frasandy   +2 more
doaj   +1 more source

Analyzing Behavioral Patterns of Bus Passengers Using Data Mining Methods (Case Study: Rapid Transportation Systems) [PDF]

open access: yesJournal of Applied Research on Industrial Engineering, 2023
The aim of analyzing passengers' behavioral patterns is providing support for transportation management. In other words, to improve services like scheduling, evacuation policies, and marketing, it is essential to understand spatial and temporal patterns ...
Amir Daneshvar   +3 more
doaj   +1 more source

Enriching smart card data with the trip purpose attribute

open access: yesJournal of Public Transportation, 2023
Planning public transport highly relies on the availability, quantity and quality of travel demand data of passengers. In the last two decades, smart card data has provided the opportunity to create comprehensive travel demand data as a byproduct of a ...
Hamed Faroqi   +3 more
doaj   +1 more source

E-Governance and Public Services in Local Governments: Study of The Taspen Smart Card Programfor Pension Fund Services in Makassar City and Pinrang Regency

open access: yesJurnal Studi Pemerintahan, 2023
This study aims to analyze the implementation of e-Government through Taspen Smart Card Program in pension fund services of State Civil Service. This study used a combination method of concurrent triangulation design (a balanced mix of quantitative and ...
Lukman Nul Hakim Amran Saputra   +3 more
doaj   +1 more source

A Deterministic Methodology Using Smart Card Data for Prediction of Ridership on Public Transport

open access: yesApplied Sciences, 2022
In the present study, we propose a methodology that predicts the number of passengers on new public transport lines based on smart card data and an optimal path finding algorithm.
Minhyuck Lee, Inwoo Jeon, Chulmin Jun
doaj   +1 more source

Mobility Irregularity Detection with Smart Transit Card Data [PDF]

open access: yes, 2020
Identifying patterns and detecting irregularities regarding individual mobility in public transport system is crucial for transport planning and law enforcement applications (e.g., fraudulent behavior). In this context, most of recent approaches exploit similarity learning through comparing spatial-temporal patterns between normal and irregular records.
Xuesong Wang 0002   +5 more
openaire   +1 more source

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