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Abstract

Using Greater Jakarta Commuter Survey data published by Statistics Indonesia in 2014, this study aims to identify the factors affecting commuting workers to choose the mode of transportation for work and the marginal effect of these factors. Estimation results from logistic regression indicate that income and workdays are not significantly affecting the commuting workers mode choice. The number of modes used has the highest impact on the probability of private vehicle and motorcycle use over public transport. As age, time travel, and travel distance increase, commuter worker less likely to use private vehicle.

Bahasa Abstract

Menggunakan data Survei Komuter Jabodetabek yang diterbitkan oleh Badan Pusat Statistik pada tahun 2014, penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang memengaruhi pekerja komuter untuk memilih moda transportasi untuk bekerja dan efek marginal dari faktor-faktor tersebut. Hasil estimasi dari regresi logistik menunjukkan bahwa pendapatan dan hari kerja tidak secara signifikan memengaruhi pilihan moda transportasi pekerja komuter. Jumlah moda yang digunakan memiliki dampak tertinggi pada probabilitas penggunaan kendaraan pribadi dan sepeda motor dibandingkan angkutan umum. Seiring dengan bertambahnya usia, lama, dan jarak perjalanan, pekerja komuter cenderung tidak menggunakan kendaraan pribadi.

References

[1] Arbues, P., Banos, J. F., Mayor, M., & Suarez, P. (2016). Determinants of ground transport modal choice in long-distance trips in Spain. Transportation Research Part A: Policy and Practice, 84, 131-143. doi: https: //doi.org/10.1016/j.tra.2015.06.010.

[2] Artıs, M., Romanı, J., & Surinach, J. (2000). Determinants of individual commuting in Catalonia, 1986-91: Theory and empirical evidence. Urban Studies, 37(8), 1431-1450. doi: https://doi.org/10.1080/2F00420980020080191.

[3] Ashalatha, R., Manju, V. S., & Zacharia, A. B. (2013). Mode choice behavior of commuters in Thiruvananthapuram city. Journal of Transportation Engineering, 139(5), 494-502. doi: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000533.

[4] Bastarianto, F. F., Irawan, M. Z., Choudhury, C., Palma, D., & Muthohar, I. (2019). A tour-based mode choice model for commuters in Indonesia. Sustainability, 11(3), 788. doi: https://doi.org/10.3390/su11030788.

[5] Bergantino, A. S., & Madino, L. (2015). The travel-to-work. Which factors matter? An analysis on regional labor market in UK. Conference Paper, ERSA 2015 - 55th Congress of the European Regional Science Association, 25-28 August 2015, Lisbon, Portugal.

[6] Bernetti, G., Longo, G., Tomasella, L., & Violin, A. (2008). Sociodemographic groups and mode choice in a middlesized European city. Transportation Research Record, 2067(1), 17-25. doi: https://doi.org/10.3141/2F2067-03.

[7] Bisnis.com. (2019, 1 Januari). Ganjil genap dilanjutkan 2019, berlaku mulai 2 Januari di 9 ruas jalan. Bisnis.com. Diakses 4 Agustus 2019 dari https://jakarta.bisnis.com/read/20190101/77/874377/ ganjil-genap-dilanjutkan-2019-berlaku-mulai-2-januari-di- 9-ruas-jalan.

[8] BPS. (2014). Statistik komuter Jabodetabek: Hasil survei komuter Jabodetabek 2014. Jakarta: Badan Pusat Statistik.

[9] BPS Provinsi Banten. (2015). Banten dalam Angka = Banten in Figure 2015. Serang: Badan Pusat Statistik Provinsi Banten.

[10] BPS Provinsi DKI Jakarta. (2015). Jakarta dalam Angka = Jakarta in Figure 2015. Jakarta: Badan Pusat Statistik Provinsi DKI Jakarta.

[11] BPS Provinsi Jawa Barat. (2015). Jawa Barat dalam Angka = Jawa Barat in Figures 2015. Bandung: Badan Pusat Statistik Provinsi Jawa Barat.

[12] Buehler, R. (2011). Determinants of transport mode choice: a comparison of Germany and the USA. Journal of Transport Geography, 19(4), 644-657. doi: https: //doi.org/10.1016/j.jtrangeo.2010.07.005.

[13] Chotib, C. (2019). Analisis pemilihan moda angkutan umum atau pribadi pekerja mobilitas non-permanen di sepuluh wilayah metropolitan Indonesia. Journal of Regional and Rural Development Planning, 3(2), 142-156. doi: https://doi.org/10.29244/jp2wd.2019.3.2.142-156.

[14] Chuen, O. C., Karim, M. R., & Yusoff, S. (2014). Mode choice between private and public transport in Klang Valley, Malaysia. The Scientific World Journal, 2014. doi: https: //doi.org/10.1155/2014/394587.

[15] de Dios Ortuzar, J., & Willumsen, L. G. (2011). Modelling transport (4th edition). John Wiley & Sons.

[16] De Witte, A., Hollevoet, J., Dobruszkes, F., Hubert, M., & Macharis, C. (2013). Linking modal choice to motility: A comprehensive review. Transportation Research Part A: Policy and Practice, 49, 329-341. doi: https: //doi.org/10.1016/j.tra.2013.01.009.

[17] Dwianthony, P. (2014, 25 Mei). 3 in 1 di wilayah DKI Jakarta. www.skyscanner.co.id. Diakses 4 Agustus 2019 dari https:// www.skyscanner.co.id/berita/3-1-di-wilayah-dki-jakarta.

[18] Eliasson, K., Lindgren, U., & Westerlund, O. (2003). Geographical labour mobility: migration or commuting?. Regional Studies, 37(8), 827-837. doi: https: //doi.org/10.1080/0034340032000128749.

[19] Ferreira, A., Antunes, A., & Seco, A. (2006). Planning implications of the Oporto region inter-municipal travel patterns. Conference paper, Joint International Conference on Computing and Decision Making in Civil and Building Engineering (pp. 2625-2635), June 14-16, 2006, Montreal, Canada.

[20] Gujarati, D. N., & Porter, D. (2009). Basic Econometrics (5th edition). New York: McGraw-Hill/Irwin.

[21] Habib, K. M. N., Day, N., & Miller, E. J. (2009). An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model. Transportation Research Part A: Policy and Practice, 43(7), 639-653. doi: https://doi.org/10.1016/j.tra.2009.05.001.

[22] Han, Y., Guan, H. Z., & Xue, M. (2011). Preferred mode choice model for commuter purpose based on multinominal logit model. Applied Mechanics and Materials, 97-98, 570-575. doi: https://doi.org/10.4028/www.scientific.net/AMM.97- 98.570.

[23] Hazans, M. (2004). Does commuting reduce wage disparities?. Growth and Change, 35(3), 360-390. doi: https://doi.org/10.1111/j.1468-2257.2004.00253.x.

[24] Howard, E. (2013). Garden cities of to-morrow. Routledge.

[25] Hu, X., Zhao, L., & Wang, W. (2015). Impact of perceptions of bus service performance on mode choice preference. Advances in Mechanical Engineering, 7(3), 1-11. doi: https://doi.org/10.1177/2F1687814015573826.

[26] Hugo, G. (1975). Population mobility in West Java, Indonesia. (Doctoral Dissertation, Australian National University). doi: https://doi.org/10.25911/5d70ed56dd771.

[27] Hussain, H. D., Mohammed, A. M., Salman, A. D., Rahmat, R. A. B. O. K., & Borhan, M. N. (2017). Analysis of transportation mode choice using a comparison of artificial neural network and multinomial logit models. ARPN Journal of Engineering and Applied Sciences, 12(5), 1483-1493.

[28] Jiang, K., Zhang, N., & Feng, Z. (2014). A binary logit model for commute mode choice: A case study of Hefei. Conference Paper, 14th COTA International Conference of Transportation Professionals: Safe, Smart, and Sustainable Multimodal Transportation Systems (pp. 3029-3040), 4-7 July 2014, Changsha, China.

[29] Jun, M. J., Kim, J. I., Kwon, J. H., & Jeong, J. E. (2013). The effects of high-density suburban development on commuter mode choices in Seoul, Korea. Cities, 31, 230-238. doi: https://doi.org/10.1016/j.cities.2012.06.016.

[30] Kementerian Perhubungan. (2018). Laporan Kinerja Kementerian Perhubungan Tahun 2017. Jakarta: Kementerian Perhubungan. Diakses 4 Agustus 2019 dari http://ppid.dephub. go.id/files/lakip/laporan-kinerja-kemenhub-2017.pdf.

[31] Kusuma Dewi, R. (2018). Pemodelan pemilihan moda transportasi pada komuter di Jabodetabek menggunakan Bayesian Network dan Regresi Logistik Polytomous (Masters thesis, Institut Teknologi Sepuluh Nopember).

[32] Loo, B. P., & Chow, A. S. (2011). Jobs-housing balance in an era of population decentralization: An analytical framework and a case study. Journal of Transport Geography, 19(4), 552-562. doi: https://doi.org/10.1016/j.jtrangeo.2010.06.004.

[33] Lucas, T. Y., Archilla, A. R., & Papacostas, C. S. (2007). Mode choice behavior of elderly travelers in Honolulu, Hawaii. Transportation Research Record: Journal of the Transportation Research Board, 2013(1), 71-79. doi: https://doi.org/10.3141/2F2013-10.

[34] Ma, T. Y. (2015). Bayesian networks for multimodal mode choice behavior modelling: a case study for the cross border workers of Luxembourg. Transportation Research Procedia, 10, 870-880. doi: https://doi.org/10.1016/j.trpro.2015.09.040.

[35] McKenzie, B. (2013, January). County-to-county commuting flows: 2006-10. US Census Bureau. Diakses 4 Agustus 2019 dari https://www.census.gov/library/working-papers/2013/ acs/2013-McKenzie.html.

[36] McLafferty, S. (1997). Gender, race, and the determinants of commuting: New York in 1990. Urban Geography, 18(3), 192-212. doi: https://doi.org/10.2747/0272-3638.18.3.192.

[37] Merdeka.com. (2016, 29 Maret). Sejarah pemberlakuan 3 in 1 di Jakarta. Merdeka.com. Diakses 4 Agustus 2019 dari https://www.merdeka.com/jakarta/ sejarah-pemberlakuan-3-in-1-di-jakarta.html.

[38] Muro-Rodrıguez, A. I., Perez-Jimenez, I. R., & Gutierrez- Broncano, S. (2017). Consumer behavior in the choice of mode of transport: a case study in the Toledo- Madrid corridor. Frontiers in Psychology, 8, 1011. doi: https: //doi.org/10.3389/fpsyg.2017.01011.

[39] Ng, W. S., & Acker, A. (2018). Understanding urban travel behaviour by gender for efficient and equitable transport policies. International Transport Forum (ITF) Discussion Paper, 2018-01. Organisation for Economic Cooperation and Development (OECD). Diakses 5 Agustus 2019 dari https://www.itf-oecd.org/sites/default/files/docs/ urban-travel-behaviour-gender.pdf.

[40] Nicholson, W., & Snyder, C. (2007). Intermediate microeconomics and its application (11th edition). South-Western Cengage Learning.

[41] Okezone.com. (2016). Awal mula penerapan sistem ganjil genap di Jakarta. Okezone.com. Diakses 5 Agustus 2019 dari https://news.okezone.com/read/2016/06/28/338/1427252/ awal-mula-penerapan-sistem-ganjil-genap-di-jakarta.

[42] Persyn, D., & Torfs, W. (2016). A gravity equation for commuting with an application to estimating regional border e ects in Belgium. Journal of Economic Geography, 16(1), 155-175. doi: https://doi.org/10.1093/jeg/lbv003.

[43] Pongprasert, P., & Kubota, H. (2017). Switching from motorcycle taxi to walking: A case study of transit station access in Bangkok, Thailand. IATSS Research, 41(4), 182-190. doi: https://doi.org/10.1016/j.iatssr.2017.03.003.

[44] PPID-Kemenhub. (2015). Rencana Induk Transportasi Jabodetabek (RITJ). Pejabat Pengelola Informasi dan Dokumentasi Kementerian Perhubungan. Diakses 5 Agustus 2019 dari http://ppid.dephub.go.id/files/datalitbang/bptj/ laporan RITJ 30-6-2015 AR.pdf. [

45] PT KCI. (2017). Laporan Tahunan (Annual Report) 2017. Jakarta: PT Kereta Commuter Indonesia.

[46] Ramadhiani, A. (2018, 25 Februari). Ini 10 kota termacet di Indonesia. Kompas.com. Diakses 21 November 2018 dari https://properti.kompas.com/read/2018/02/25/182046621/ ini-10-kota-termacet-di-indonesia.

[47] Richter, C., & Keuchel, S. (2011). Influences of Service Quality on the Choice of Transport Mode. Conference Paper, 9th World Congress on Railway Research, May 22-26, 2011, Lille, France.

[48] Setyodhono, S. (2017). Faktor yang mempengaruhi pekerja komuter di jabodetabek menggunakan moda transportasi utama. Warta Penelitian Perhubungan, 29(1), 21-32. doi: http://dx.doi.org/10.25104/warlit.v29i1.326.

[49] Soehodho, S., & Rahadiani, F. (2012). Transport Mode Choice by Land Transport Users in Jabodetabek (Jakarta-Bogor- Depok-Tangerang-Bekasi): An Urban Ecology Analysis. In 2nd International Conference on Electrical, Electronics and Civil Engineering (ICEECE’2012) (pp. 177–181), April 28-29, 2012, Singapore.

[50] Tamin, O. Z. (2000). Perencanaan dan pemodelan transportasi (Edisi kedua). Penerbit ITB.

[51] Wang, Q., & Hu, H. (2017). Rise of Interjurisdictional Commuters and Their Mode Choice: Evidence from the Chicago Metropolitan Area. Journal of Urban Planning and Development, 143(3), 05017004. doi: https://doi.org/10.1061/(ASCE)UP.1943-5444.0000381.

[52] Weng, J., Tu, Q., Yuan, R., Lin, P., & Chen, Z. (2018). Modeling mode choice behaviors for public transport commuters in Beijing. Journal of Urban Planning and Development, 144(3), 05018013. doi: https://doi.org/10.1061/(ASCE)UP.1943-5444.0000459.

[53] Zhou, J. (2016). Proactive sustainable university transportation: Marginal effects, intrinsic values, and university students’ mode choice. International Journal of Sustainable Transportation, 10(9), 815-824. doi: https: //doi.org/10.1080/15568318.2016.1159357.

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