ANALYSIS OF THE DETERMINANTS OF GOJEK DRIVERS INCOMEIN DENPASAR CITY
Keywords:
Motobike ride hailing, fare, working hour, transaction, incentiveAbstract
Community mobility requires adequate transportation services. The rapid advancement of technology has led to the emergence of online transportation, particularly application-based services that simplify access to mobility. One prominent example is online motorcycle taxis, such as Gojek, which not only offer transportation and delivery services but also create job opportunities with flexible working hours as a key attraction. The income earned by Gojek drivers is determined by various factors, including fares, working hours, the number of transactions completed, and performance-based incentives. This study investigates how these fares, working hours, number of transactions, and incentives affect the income of Gojek drivers in Denpasar City. This study aims to examine the influence of fares, working hours, number of transactions, and incentives on the income of Gojek drivers in Denpasar City, both simultaneously and individually, and to identify the most dominant factor affecting their income. The research was conducted in Denpasar City with a sample of 96 Gojek drivers selected through a convenience (incidental) sampling technique. Primary data were collected through observation, structured and unstructured interviews, as well as documentation. The research data were analyzed using multiple linear regression, supported by classical assumption tests, F-tests to assess the joint significance of the variables, t-tests to evaluate individual variable effects, and a dominance test to identify the most influential factor. The results show that fares, working hours, number of transactions, and incentives together significantly affect the income of Gojek drivers. In partial analysis, fares, number of transactions, and incentives show a positive and significant effect on income, whereas working hours have a positive but statistically insignificant influence. Among all the variables analyzed, the number of transactions is identified as the most dominant factor influencing the income of Gojek drivers in Denpasar City.
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References
Aisy-Assariy, N., et al. (2023). Dampak Kenaikan Harga Bahan Bakar Minyak, Jam Kerja, dan Insentif terhadap Pendapatan Driver Transportasi Online di Kota Makassar. Bulletin of Economic Studies (BEST), 3(3), hal. 123-131.
Badan Pusat Statistik Provinsi Bali. (2024). Banyaknya Kendaraan Menurut Kabupaten/Kota di Provinsi Bali (Unit), 2022-2023. bali.bps.go.id.
Badan Pusat Statistik (2024). Perkembangan Jumlah Kendaraan Bermotor Menurut Jenis (Unit), 2021-2022. bps.go.id.
Badan Pusat Statistik Provinsi Bali. (2024). Persentase Penduduk Usia 5 Tahun ke Atas yang Mengakses Teknologi Informasi dan Komunikasi (TIK) dalam 3 Bulan Terakhir Menurut Kabupaten/Kota di Provinsi Bali, 2019-2023. bali.bps.go.id.
Badan Pusat Statistik. (2024). Statistik Telekomunikasi Indonesia 2023. Bps.go.id.
Bisma-Putra, C., Kartika-Yudha, I. M. E. (2023). Analisis Pendapatan Driver Gojek Pada Saat Pandemi Covid 19 Di Kota Denpasar. Media Informasi Penelitian Kabupaten Semarang, 5(1), hal. 265-287.
Elton-Wanda, M., Prasetyanta, A. (2021). Analisis Pengaruh Pengalaman Kerja, Jam Kerja, dan Jumlah Orderan terhadap Pendapatan Driver Ojek Online Di Kota Yogyakarta. Equilibrium Jurnal Bisnis & Akuntansi, 15 (1), hal. 34-48.
Fakhriyah, P. (2020). Pengaruh Layanan Transportasi Online (Gojek) Terhadap Perluasan Lapangan Kerja Bagi Masyarakat Di Kota Cimahi. Jurnal Comm-Edu, 3(1), hal. 34-41.
Hartadi, A. S., Rusdiansyah. (2019). Pengaruh Tarif, Jam Kerja dan Jumlah Orderan Terhadap Pendapatan Driver Go-Jek di Kota Banjarmasin. elton, 2(1), hal. 231-243.
Hoang-Tung, N., et. al (2024). Ride-hailing service availability and private transportation mode usage in a motorcycle-based city: Evidence from Hanoi. Transportation Research Interdisciplinary Perspectives, hal. 1-14.
Institute for Development of Economics and Finance. (2022). Survey Result: Mengupas Industri Transportasi dan Logistik Online di Indonesia Pasca Pandemi. Indef.or.id. https://indef.or.id/wp-content/uploads/2023/03/PPT-Esther-Sri-Astuti-Hasil-Studi-Transportasi-dan-Logistik-Online-di-Indonesia-Pasca-Pandemi.pdf
Irawan, M. Z., et. al (2022). Mapping the motorcycle-based ride-hailing users in Yogyakarta: An analysis of socio-economic factors and preferences. Asian Transport Studies, hal. 1-10.
Kurniawan, M. F., Marhaeni, A. A. I. N. (2023). Analysis of Factors Affecting Go-Jek Driver Income during the Covid-19 Pandemic in Denpasar City. European Journal of Development Studies, 3(2), hal. 52-58.
Magda, I., Lipowska,K. (2021). Flexibility of Working Time Arrangements and Female Labor Market Outcome. IZA – Institute of Labor Economics. https://www.iza.org/publications/dp/14812/flexibility-of-working-time-arrangements-and-female-labor-market-outcome.
Mankiw, N. G. (2006). Makroekonomi Edisi Keenam. Jakarta: Penerbit Airlangga
Marhaeni, Manuati Dewi. (2004). Buku Ajar Ekonomi Sumber Daya Manusia. Denpasar: Fakultas Ekonomi Universitas Udayana.
Mulyadi, S. (2003). Ekonomi Sumber Daya Manusia Dalam Perspekstif Pembangunan. Jakarta: Rajagrafindo Persada.
Navilla, M. S. (2021). Analisis Pendapatan Driver Ojek Online Di Masa Pandemi Covid 19. COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat, 1 (8), hal. 12-16.
Oktavian, M. N. D., et. al. (2023). Pengaruh Ojek Online: Faktor Faktor Yang Mempengaruhi Pendapatan Driver Gojek Dan Grab Di Kota Yogyakarta Tahun 2023 Dengan Metode Kualitatif. Jurnal Ilmiah Akuntansi’45, 4(1), hal. 195-204.
Priyono., Marnis (2008). Manajemen Sumber Daya Manusia. Sidoarjo: Zifatama Publisher. https://www.binadarma.ac.id/wp-content/uploads/2016/03/1.-BUKU-MSDM-PRI-MARNIS.pdf
Putri, N. M. K. (2025). Denpasar Macet, Jumlah Kendaraan Lebih Banyak ketimbang Penduduk. Travel.detik.com. https://travel.detik.com/travel-news/d-7741977/denpasar-macet-jumlah-kendaraan-lebih-banyak-ketimbang-penduduk
Rupbianti, V. (2024). Pengaruh Jam Kerja, Bonus Insentif Dan Area Hotspot Terhadap Pendapatan Mitra Pengemudi Grab Di Kota Tulungagung. Jurnal Mahasiswa Manajemen, Bisnis, Entrepreneurship, 3(1), hal. 39-46
Samuelson, P.A., Nordhaus, W. D. (2001). Microeconomics Seventeenth Edition. New York: McGraw-Hill.
Sugiyono. (2018). Metode Penelitian Bisnis (Pendekatan Kuantitatif, Kualitatif, Kombinasi R&D). Bandung: Penerbit Alfabeta.
Suyana-Utama, M. (2017). Buku Ajar Ekonometrika. Denpasar: Sastra Utama.
Syahreza, D. S., et. al. (2024). Perubahan Skema Insentif Pada PT Grab Dan Gojek: DampakTerhadap Kepuasan Driver. Economic Review Journal, 3 (3), hal. 2004-2020.
Usman. (2021). Analisis Faktor-Faktor yang Mempengaruhi Pendapatan Driver Go-Ride pada Masa Pandemi Covid-19 di Gorontalo. Al-Buhuts e-Journal, 17 (1), hal. 35-51.
Watung, M. P., et al. (2020). Analisis Perbandingan Pendapatan Ojek Konvensional Dan Ojek Online Di Kota Manado. Jurnal Berkala Ilmiah Efisiensi, 20 (3), hal. 126-139.
Wenehenubun, L. Y., et al. (2023). Pengaruh Jam Kerja, Tarif Dan Jumlah Orderan terhadap Pendapatan Driver Online (Indriver) Di Kota Manado. Jurnal Berkala Ilmiah Efisiensi, 23(8), hal. 97-108.
Zahra, A. F., Bustamam, N. (2024). Analisis Faktor - Faktor Yang Mempengaruhi Pendapatan Driver Motor Go-Jek Di Pekanbaru. Management Studies and Entrepreneurship Journal, 5(1), hal. 3019-3025.