APLIKASI GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) PADA PEMODELAN VOLUME KENDARAAN MASUK TOL SEMARANG
| Main Authors: | Anggraeni, Dian, Prahutama, Alan, Andari, Shofi |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
Departemen Statistika FSM Undip
, 2013
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| Online Access: |
http://ejournal.undip.ac.id/index.php/media_statistika/article/view/7639 http://ejournal.undip.ac.id/index.php/media_statistika/article/view/7639/6293 |
Daftar Isi:
- Time series data from neighboring separated location often associated both spatially and through time. Generalized space time autoregrresive (GSTAR) model is one of the most common used space-time model to modeling and predicting spatial and time series data. This study applied GSTAR to modeling vehicle volume entering four tollgate (GT) in Semarang City: GT Muktiharjo, GT Gayamsari, GT Tembalang, and GT Manyaran. The data was collected by month from 2003 to 2009. The best model provided by this study is GSTAR (21)-I(1,12) uniformly weighted with the smallest REMSE mean 76834. Key words: GSTAR, Vehicle Volume, Space-Time Model