Job Autonomy, Platform Algorithmic Control, dan Work-Life Balance Terhadap Kinerja Karyawan Pekerja Gig Grab Sektor Transportasi di Cirebon - Chandra Anggara; Muhamad Alwi (Al-Kharaj: Jurnal Ekonomi, Keuangan & Bisnis Syariah, 2026)
Digital transformation has changed the global employment landscape through the emergence of the gig economy, with Grab as one of the largest platforms in Indonesia. In Cirebon City, there are 4,560 active Grab partners who face the paradox between work flexibility and the reality of strict algorithmic control. This study aims to analyze the influence of job autonomy, platform algorithmic control, and work-life balance on the performance of Grab partners in Cirebon City. The study used a quantitative approach with a multiple linear regression method on 150 active Grab partner respondents selected using a purposive sampling technique. Data were collected through a structured 5-point Likert scale questionnaire that had been tested for validity and reliability, then analyzed using SPSS version 22. The results showed that job autonomy had a significant positive effect on performance with a coefficient of 0.424, work-life balance had a significant positive effect with a coefficient of 0.344, while platform algorithmic control had a minimal positive effect with a coefficient of 0.038. Simultaneously, all three variables had a significant effect, with the model Y = 9.578 + 0.424X₁ + 0.038X₂ + 0.344X₃. Job autonomy was the most dominant variable influencing performance, followed by work-life balance and platform algorithmic control. This study provides a theoretical contribution by integrating the Job Characteristics Model, Organizational Control Theory, and Conservation of Resources Theory in the context of the Indonesian gig economy. Practically, the results provide recommendations for Grab Indonesia to increase algorithm transparency and provide greater autonomy to partners. This study also provides an empirical basis for the government in formulating more comprehensive regulations for protecting digital platform workers.