Manajemen SDM Inovatif dan Kinerja Pekerja Gig: Peran Mediasi Work Engagement dan Moderasi Pelemahan Algorithmic Management
DOI:
https://doi.org/10.32500/jematech.v9i2.11343Keywords:
Gig Economy, Innovative HRM, Work Engagement, Algorithmic Management, Worker PerformanceAbstract
Digitalisasi yang masif mendorong dominasi ekonomi gig di pasar kerja informal Indonesia, yang memicu paradoks antara fleksibilitas waktu dan kerentanan perlindungan kerja. Penelitian ini bertujuan untuk menganalisis pengaruh praktik Manajemen Sumber Daya Manusia (MSDM) inovatif terhadap kinerja pekerja gig, dengan menguji peran mediasi work engagement dan peran moderasi algorithmic management. Menggunakan pendekatan kuantitatif eksplanatori, data dikumpulkan melalui kuesioner terstruktur dari 150 responden pengemudi transportasi daring di Yogyakarta. Analisis data menggunakan metode Partial Least Squares Structural Equation Modeling (PLS-SEM) dibantu perangkat lunak SmartPLS 4. Hasil pengujian hipotesis menunjukkan bahwa praktik Manajemen SDM inovatif (pelatihan digital dan insentif transparan) berpengaruh positif signifikan terhadap work engagement ( = 0.458, p = 0.000) dan kinerja pekerja ( = 0.769, p = 0.002). Selanjutnya, work engagement terbukti memediasi hubungan antara Manajemen SDM inovatif dan kinerja secara parsial ( = 0.173, p = 0.002). Temuan krusial dan kebaruan dalam penelitian ini membuktikan bahwa algorithmic management memiliki efek moderasi negatif yang signifikan ( = -0.127, p = 0.016). Kontrol digital yang terlampau ketat dan kaku justru memperlemah dampak positif dari inisiatif MSDM inovatif terhadap kinerja. Penelitian ini merekomendasikan pentingnya penyusunan etika algoritma yang humanis dan regulasi inklusif guna menjaga keberlanjutan ekosistem kerja digital dan kesejahteraan pekerja.
References
Bakker, A. B., & Demerouti, E. (2007). The job demands‐resources model: State of the art. Journal of Managerial Psychology, 22(3), 309–328.
Bondarouk, T., Ruël, H. J. M., & van der Heijden, B. (2009). E-HRM Effectiveness in a Public Sector Organization: A Multi-Stakeholder Perspective. International Journal of Human Resource Management - INT J HUM RESOUR MANAG, 20, 578–590. https://doi.org/10.1080/09585190802707359
Charmelita, E. R., & Wardani, S. (2024). Perlindungan Hukum Bagi Driver Grab Yang Mengalami Pesanan Fiktif Pada Era Gig Economy Di Kabupaten Banyumas. COLLEGIUM STUDIOSUM JOURNAL, 7(2), 2024.
Chidiebere, A. M., Roseline, U. M., & Veronica, C. O. (2025). International Human Resource Management in The Gig Economy. Global Journal of Research in Business Management, 05(05), 96–104. https://doi.org/10.5281/zenodo.17440090
Chigbu, B. I. (2026). Algorithmic management in the global gig economy: an interdisciplinary systematic literature review and critical discourse analysis. Frontiers in Sociology, 11, 1743445.
CNN Indonesia. (2024, March 27). Menilik Rencana Menaker Buat Aturan Baru soal Perlindungan Ojol. Cnnindonesia.Com. https://www.cnnindonesia.com/ekonomi/20240327064851-92-1079416/menilik-rencana-menaker-buat-aturan-baru-soal-perlindungan-ojol
DPRD DIY. (2025, May 20). Massa Ojol Tuntut Kenaikan Tarif dan Regulasi yang Berpihak, DPRD DIY Pastikan Aspirasi Diteruskan ke Pusat. Dprd-Diy.Go.Id. https://www.dprd-diy.go.id/massa-ojol-tuntut-kenaikan-tarif-dan-regulasi-yang-berpihak-dprd-diy-pastikan-aspirasi-diteruskan-ke-pusat/
Goto. (2026, February 17). GoTo Launches Four Strategic Initiatives to Support Driver-Partner Well-being. Gotocompany.Com. https://www.gotocompany.com/en/news/press/goto-launches-four-strategic-initiatives-to-support-driver-partner-well-being
Hartoto, A. (2026, January 17). Grab for Indonesia: IDR 100 billion commitment program: A Story in three acts. Observerid.Com. http://observerid.com/grab-for-indonesia-idr-100-billion-commitment-program-a-story-in-three-acts/
Huda, N., Nurhyati, Y., & Ansori, F. (2025). Perlindungan Keselamatan dan Kesehatan Kerja bagi Pengemudi Ojek Online dalam Sistem Gig Economy. Jurnal Penegakan Hukum Indonesia, 6. https://doi.org/10.51749/jphi.v6i3.147
Koopmans, L., Bernaards, C., Hildebrandt, V., Schaufeli, W., De Vet, H., & van der Beek, A. (2011). Conceptual Frameworks of Individual Work Performance. Journal of Occupational and Environmental Medicine / American College of Occupational and Environmental Medicine, 53, 856–866. https://doi.org/10.1097/JOM.0b013e318226a763
Kurniawan, D., & Rojabi, M. A. (2026). Fastwork: Transformasi Ekosistem Ekonomi Gig di Era Baru. Afdan Rojabi Publisher.
Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers. https://doi.org/10.1145/2702123.2702548
Lin, Q., Sun, R., & Zhu, Q. (2025). Perceived algorithmic control and gig workers’ work engagement: assessing the mediating role of psychological empowerment and the moderating effect of deep acting. BMC Psychology, 13(1), 1237.
Meijerink, J., & Keegan, A. (2019). Conceptualizing human resource management in the gig economy: Toward a platform ecosystem perspective. Journal of Managerial Psychology, 34(4), 214–232.
Pramana, R. L., & Sugiyanto, S. (2024). Tantangan Pemerintah Indonesia Dalam Menghadapi Gig Economy. Jurnal Ekonomi Dan Bisnis, 2(4), 857–874.
Purba, M. F. C. M., Sari, E. T., & Purba, L. P. (2026). Beyond Flexibility: Management Innovation and Algorithmic Control in the Gig Economy Era. Airlangga Journal of Innovation Management, 7(1), 188–202. https://doi.org/10.20473/ajim.v7i1.86884
Putri, M. A., & Bahruddin. (2023). Kelayakan Kerja Driver Gojek Yogyakarta: Persepsi Subjektif sebagai Representasi Pekerja Gig. Universitas Gadjah Mada.
Ramasamy, I., & AS, S. (2026). Exploring the influence of HR practices on gig workers engagement: a serial mediation moderation model through IPMA analysis. Cogent Business & Management, 13(1), 2650855.
Rivandra, R., Valentina, B., Terry, M., & Levina, A. (2025, March 18). Who Are Gig Workers? Insights from Indonesia. Idinsight.Org. https://www.idinsight.org/article/who-are-gig-workers-insights-from-indonesia/
Schaufeli, W., Salanova, M., & González-Romá, V. (2002). The Measurement of Engagement and Burnout: A Two Sample Confirmatory Factor Analytic Approach. Journal of Happiness Studies, 3, 71–92. https://doi.org/10.1023/A:1015630930326
Sharma, S. (2026). Human Resource Management in the Gig Economy: A study on sustainable HRM practices in Gig workers in the era of Algorithmic control. International Research Journal on Advanced Engineering and Management (IRJAEM), 4, 487–492. https://doi.org/10.47392/IRJAEM.2026.0077
Unesa. (2025, July 1). Tarif Ojol Naik 15%: Rincian Kenaikan Biaya, Pro dan Kontra, serta Dampak Bagi Pengguna serta Driver. Pendidikan-Sains.Fmipa.Unesa.Ac.Id. https://pendidikan-sains.fmipa.unesa.ac.id/post/tarif-ojol-naik-15-rincian-kenaikan-biaya-pro-dan-kontra-serta-dampak-bagi-pengguna-serta-driver
Wahyuni, R. N. T., & Asy-Syifa, A. (2025). The Impact of Kartu Prakerja Program Participation on the Decision to Become a Gig Worker and Gig Worker Earnings in Indonesia. Jurnal Ketenagakerjaan, 20(3). https://doi.org/10.47198/jnaker.v20i3.539
Wen, Y., Lv, B., & Liu, J. (2026). Enhancing Work Engagement in the Gig Economy: Evidence from Platform Workersx. Sustainability (Switzerland), 18(5). https://doi.org/10.3390/su18052501
Wiener, M., Cram, W., & Benlian, A. (2023). Algorithmic control and gig workers: A legitimacy perspective of Uber drivers. European Journal of Information Systems, 32, 485–507. https://doi.org/10.1080/0960085X.2021.1977729
Wood, A., Graham, M., Lehdonvirta, V., & Hjorth, I. (2018). Good Gig, Bad Big: Autonomy and Algorithmic Control in the Global Gig Economy. Work, Employment and Society, 33, 095001701878561. https://doi.org/10.1177/0950017018785616
Zareka, A. Muh. Z., Hidayatullah, A., Sakina, D., Cotva, B. M., & Budiasih. (2025). What Drives Gig Workers’ Welfare in Indonesia? Evidence from a Panel Data Regression 2018–2023. Jurnal Ketenagakerjaan, 20(3). https://doi.org/10.47198/jnaker.v20i3.543
