PROBABILITY MODEL OF MODE SHIFT TO PUBLIC TRANSPORTATION IN BEKASI TIMUR SUB DISTRICT BASED ON USERS’ PREFERENCES

  • Ketut Dewi Martha Erli Handayeni Dept. of Urban and Regional Planning, Technology Institute of Sepuluh Nopember
  • Ginanjar Prayogo Dept. of Urban and Regional Planning, Technology Institute of Sepuluh Nopember
  • Ayu Tarviani Dewi Dept. of Urban and Regional Planning, Technology Institute of Sepuluh Nopember
Keywords: public transport, mode choice probability, motorcycle

Abstract

Nowadays, automobile usage is still dominated in some cities. In Bekasi City, mode share of public transport is only 24% and 76% for private mode (with a percentage of car use is 20%, 64% for motorcycle and 16% for others). Bekasi Timur sub-district is a highly densely populated area in Bekasi City. Therefore, the area is the zone with high trip generation and high use of motorcycles. This study aims to simulate the probability model of mode shift from motorcycle to public transport (called Angkot) use. By using binary logistic regression model, there are four main attributes that influence the mode choice, such as safety, travel time, convenience and cost. The cost has the lowest influence and not sensitive to the change of mode choice. In existing, the probability to choose public transport is only 0.03%, extremely the probability of motorcycle use reached 99,99%. Improving the safety of public transport increase the probability about 0.67% and increase up to 13.81% if decrease the travel time. The probability to use public transport will increase significantly reached 54,56% if convenience is also improved. Improving those attributes can reduce the high use of motorcycle and shift to public transportation.

Published
2018-05-22
How to Cite
Handayeni, K. D., Prayogo, G. and Dewi, A. (2018) “PROBABILITY MODEL OF MODE SHIFT TO PUBLIC TRANSPORTATION IN BEKASI TIMUR SUB DISTRICT BASED ON USERS’ PREFERENCES”, Prosiding Forum Studi Transportasi antar Perguruan Tinggi. Available at: https://ojs.fstpt.info/index.php?journal=prosiding&page=article&op=view&path[]=16 (Accessed: 17October2018).