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Kajian Karakteristik Spasial Dan Nonspasial Pengguna Ojek Daring Di Kawasan Pendidikan Tinggi Tembalang

*Puspita Dhian Nusa  -  Departemen Perencanaan Wilayah dan Kota Fakultas Teknik Universitas Diponegoro, Indonesia
Okto Risdianto Manullang  -  Departemen Perencanaan Wilayah dan Kota Fakultas Teknik Universitas Diponegoro, Indonesia

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Abstract

Technological developments are increasing from time to time and impact on all fields of life, including transportation. One of the online transportation services is online motorcycle that provides services for service users on a door to door basis. These conditions change people's travel behavior from public transportation to online transportation. The purpose of this study is to examine the variables of spatial and non-spatial characteristics that have a significant effect on the frequency of online transportation use. The research approach used is quantitative and analytical tools in the form of cross tabulation. The results of the study show that the spatial variable that is considered in determining the frequency of online transportation use is the distance of residence to local facilities. In addition, non-racial variables that have a relationship with the frequency of online transportation use are gender, age structure, motor vehicle ownership and income. The proposal is based on the results of research, related to the issue of online transportation in terms of online transportation users, the majority of whom are women, namely the need for additional features related to vehicle location, the identity of the driver who is forwarded to the family at home to ensure the safety of service users.

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  1. Amajida, F.D., 2016. Kreativitas digital dalam masyarakat risiko perkotaan: Studi tentang ojek online “Go-Jek” di Jakarta. Informasi, 46(1), pp.115–128
  2. Dias, F.F. et al., 2017. A behavioral choice model of the use of car-sharing and ride-sourcing services. Transportation, 44(6), pp.1307–1323
  3. Kato, H., 2006. Joint Resource Allocation Model of Household Consisting of a Husband, a Wife and a Child for Non-work Activities: Comparative Analysis of Tokyo and. In Presented at the 6th Swiss Transport Research Conference, Monte Verita
  4. Lyons, G. & Davidson, C., 2016. Guidance for transport planning and policymaking in the face of an uncertain future. Transportation Research Part A: Policy and Practice, 88, pp.104–116
  5. Pulungan, R.S. & Rakhmatulloh, A.R., 2018. MODEL PERMINTAAN TRANSPORTASI DARING DI PERUMNAS TLOGOSARI, KOTA SEMARANG. Universitas Diponegoro
  6. Rayle, L. et al., 2014. App-based, on-demand ride services: comparing taxi and ridesourcing trips and user characteristics in San Francisco,
  7. Sabri, A., ANALISIS PERILAKU PERJALANAN MAHASISWA DAN AKSESIBILITAS PADA PERGURUAN TINGGI DI MAKASSAR “(STUDI KASUS FAKULTAS EXACT UNHAS).”
  8. Septiani, R., Handayani, P.W. & Azzahro, F., 2017. Factors that affecting behavioral intention in online transportation service: Case study of GO-JEK. Procedia Computer Science, 124, pp.504–512
  9. Stiglic, M. et al., 2018. Computers and Operations Research Enhancing urban mobility : Integrating ride-sharing and public transit. Computers and Operations Research, 90, pp.12–21. Available at: http://dx.doi.org/10.1016/j.cor.2017.08.016
  10. Sugiyono, “Metode Penelitian Kuantitatif Kualitatif dan R&D”, (Bandung: Alfabeta, 2012),etd.repository.ugm.ac.id/downloadfile/81511/.../S3-2015-259706-chapter1.pdf

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