Estimasi Tujuan Penumpang Menggunakan Predictive Model dengan Data Smart Card
| Autor: | Inkreswari Retno Hardini, Goklas Henry Agus Panjaitan, Sita Rosida, Ekky Novriza Alam |
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| Rok vydání: | 2019 |
| Předmět: |
Service (systems architecture)
Operations research business.industry 010102 general mathematics Decision tree 010103 numerical & computational mathematics 01 natural sciences Column (database) Scheduling (computing) Need to know Public transport Performance indicator 0101 mathematics business Bus rapid transit Mathematics |
| Zdroj: | Jurnal Sistem Cerdas. 2:99-110 |
| ISSN: | 2622-8254 |
| Popis: | Bus Rapid Transit (BRT) is one of the main choices of public transportation that supports mobility of Jakarta community. As one of the main choices of public transportation, BRT should provide good service and always improve its performance. Needs for moving or mobility will cause a problem if the moving itself is heading at the same area and at the same time. That will cause some problems which are often faced in urban areas such as traffic and delay. To overcome those problems there needs to be a strategy to build good public transportation planning, besides need to know individual travel patterns to overcome problems and improve BRT service. In case to realize those plans needs to be built origin-destination (O-D) matrix. O-D matrix is a matrix that each cell is an amount of trip from the source(row) to the destination (column). O-D matrix is beneficial for analysis, design and public transportation management. O-D matrix also provides useful information like amount of trip between 2 different locations, that can be utilized as fundamental information for decision making for three levels of strategic management (long term planning), tactic (service adjustment and network development), and operational (scheduling, passenger statistic, and performance indicator). To build O-D matrix is required a predictive model that can be measured to predict passenger destination. The predictive model will be build using classification algorithms such as Decision Tree and K-Nearest Neighbor (KNN). |
| Databáze: | OpenAIRE |
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