Analysis of Transportation Selection for Travel Work

[1] Tamin O.Z. (2003), Perencanaan dan Pemodelan Transportasi, Penerbit ITB Bandung.Search in Google Scholar

[2] Sugiyono. (2012). Metode Penelitian Kuantitatif & Kualitatif. Bandung, Indonesia: Alfabeta.Search in Google Scholar

[3] Kuncoro, M. (2014). Metode Riset untuk Bisnis dan Ekonomi, 4^th edition, Jakarta, Indonesia: Erlangga.Search in Google Scholar

[4] Nasution, A.A., Azmi, Z., Siregar, I. & Erlina, I. (2018). Impact of air transport on the Indonesian economy. MATEC Web of Conferences. 236. DOI: 10.1051/matecconf/.10.1051/matecconf/Open DOISearch in Google Scholar

[5] Engebrethsen, E. & Dauzère-Pérès, S. (2019). Transportation mode selection in inventory models: A literature review. European Journal of Operational Research. 279(1), 1-25. DOI:10.1016/j.ejor.2018.11.067.10.1016/j.ejor.2018.11.067Open DOISearch in Google Scholar

[6] Frank, S., Berk, S., Hernandez, L., Hogarth, P., Shill, H.A., Siddiqi, B. & Simon, D.K. (2019). Transportation innovation to aid Parkinson disease trial recruitment. Contemporary Clinical Trials Communications. 16. DOI:10.1016/j.conctc.2019.100449.10.1016/j.conctc.2019.100449Open DOISearch in Google Scholar

[7] Khordagui, N. (2019). Parking prices and the decision to drive to work: Evidence from California. Transportation Research Part A: Policy and Practice. 130, 479-495. DOI:10.1016/j.tra.2019.09.064.10.1016/j.tra.2019.09.064Open DOISearch in Google Scholar

[8] McCormack, G.R., Koohsari, M.J., Oka, K., Friedenreich, C.M., Blackstaffe, A., Alaniz, F.U. & Farkas, B. (2019). Differences in transportation and leisure physical activity by neighborhood design controlling for residential choice. Journal of Sport and Health Science. 8(6), 532-539. DOI:10.1016/j.jshs.2019.05.004.10.1016/j.jshs.2019.05.004Search in Google Scholar

[9] Zhang, X. & Huang, H. (2019). Vehicle classification based on feature selection with anisotropic magnetoresistive sensor. IEEE Sensors Journal. 19(21), 9976-9982. DOI:10.1109/JSEN.2019.2928828.10.1109/JSEN.2019.2928828Open DOISearch in Google Scholar

[10] Jianchuan, X. (2010). Modeling the generation and organization of household non-work activity: A case study of Beijing. In International Conference on Optoelectronics and Image Processing, ICOIP 2010, 2, 8-11. DOI:10.1109/ICOIP.2010.32.10.1109/ICOIP.2010.32Search in Google Scholar

[11] Liu, Y. & Li, Y. (2018). Characteristic variables and behavior analysis of simple and complex non-work trip chains base on binary logit model. In CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation; Proceedings of the 17th COTA International Conference of Transportation Professionals, 2018-January, 3811-3821.10.1061/9780784480915.398Search in Google Scholar

[12] Xianyu, J. & Juan, Z. (2011). Generation and organization of household non-work activity stops. Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology. 11(4), 124-128.Search in Google Scholar

[13] Sahu, P. K., Sharma, G. & Guharoy, A. (2018). Commuter travel cost estimation at different levels of crowding in a suburban rail system: A case study of Mumbai. Public Transport. 10(3), 379-398. DOI: 10.1007/s12469-018-0190-6.10.1007/s12469-018-0190-6Open DOISearch in Google Scholar

[14] BARTUŠKA, Ladislav, Karel JEŘÁBEK a Li CHENGUANG. Determination of Traffic Patterns on urban roads. Communications, Žilina: Žilinská univerzita v Žilině, EDIS, 2017, roč. 19, č. 2, s. 103-108. ISSN 1335-4205.10.26552/com.C.2017.2.103-108Search in Google Scholar

[15] HANZL, Jiří, Ladislav BARTUŠKA, Elena ROZHANSKAYA a Petr PRŮŠA. Application of Floyd’s Algorithm on Transport Network of South Bohemian Region. Communications : scientific letters of the University of Žilina, Žilina: The University of Žilina, 2016, Volume 18, č. 2, s. 68-71. ISSN 1335-4205.10.26552/com.C.2016.2.68-71Search in Google Scholar