Single and Multi-Mode Choice Commuting Models in Surabaya and Sidoarjo Region
M.T.Gunawan1, Bambang Haryadi2, Bagus Hario Setiadji3

1M.T.Gunawan, Faculty of Engineering, Univ. Dayanu Ikhsanuddin, jl Yos Sudharso Bau Bau, Indonesia.
2Bambang Haryadi, Faculty of Engineering, Univ. Negeri Semarang, Jalan Sekaran, Gunung Pati, Sekaran, Gn. Pati, Kota Semarang, Jawa Tengah, Indonesia.
3Bagus Hario Setiadji, Department of Civil Engineering, Univ. Diponegoro, Jl. Prof. Soedarto, Tembalang, Kota Semarang, Jawa Tengah, Indonesia.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 27, 2020. | Manuscript published on February 10, 2020. | PP: 1343-1348 | Volume-9 Issue-4, February 2020. | Retrieval Number: C8584019320/2020©BEIESP| DOI: 10.35940/ijitee.C8584.029420
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Abstract: Large urban areas require a reliable multi-modal transport system to serve the needs of urban commuters. Urban public transport is currently still considered minimal by users of Multi mode (public transport). This has an impact on the dominance of single private modes, especially Single mode (motorcycles) that impact on city congestion, a mode that today can still be relied upon by urban commuters, to meet expectations in terms of quality of service, cost, time, experience and accessible only commuter trains. It takes effort to divert the end-user of the motorcycle to the final destination to switch to motorcycle over commuter train to get to the final destination. The study focuses on improving the comprehension of influencing factors, opportunities and models on the choice of single mode modes of multi mode switching, using the Binary Logistic Regression method with Stated Preference survey. The results Single mode user community in Surabaya and Sidoarjo willing to use the multi mode in case of improvement of service quality, affordable travel costs, travel time is adequate, and acces is enjoyable. 
Keywords: Motorcycle, Commuter Rail, Binary Logistic Regression, Stated Preference.
Scope of the Article: Regression and prediction