Studi Eksperimental Konsumsi RAM Selama Transfer Data Cloud Menggunakan Google Drive

Abstract

The rapid adoption of cloud storage services has made Google Drive a widely used platform for data storage and file transfer. However, the performance of cloud data transfer is not solely influenced by network bandwidth, but also by the utilization of local system resources, particularly Random Access Memory (RAM). This study aims to experimentally analyze RAM consumption during data transfer activities to Google Drive using real-time monitoring through the Windows Task Manager. The research employed a quantitative experimental approach involving 16 undergraduate students who used laptops with varying hardware specifications. Three video files with different sizes and durations approximately 350 MB (25 minutes), 1 GB (1 hour), and 2.8 GB (2 hours 30 minutes) were uploaded sequentially to Google Drive. RAM usage was observed under five conditions: idle state, upload of each file size, and peak memory usage. The results indicate that RAM consumption increases proportionally with file size and upload duration. Devices with limited RAM capacity, particularly entry-level laptops, experienced significant memory utilization reaching near maximum capacity, which negatively affected system responsiveness. In contrast, mid-range and high-end laptops demonstrated more stable RAM usage and maintained overall system performance during prolonged upload activities. These findings confirm that RAM capacity plays a crucial role in ensuring stable and efficient cloud data transfer. This study provides empirical evidence highlighting the importance of memory resources in cloud-based computing environments and offers practical insights for selecting appropriate hardware configurations to support intensive cloud storage activities.