Penerapan Virtual Memory terhadap Kinerja CPU, GPU, dan Respons Multitasking pada Windows 10

Authors

  • Fauzia Fredella Akademi Manajemen Informatika dan Komputer (AMIK) Bukittinggi
  • Ulya Rahman Akademi Manajemen Informatika dan Komputer (AMIK) Bukittinggi

DOI:

https://doi.org/10.61132/mars.v3i5.1133

Keywords:

Computer Performance, GPU, Multitasking Response, Virtual Memory, Windows 10

Abstract

The limitation of physical memory (RAM) is a primary constraint hindering optimal performance in modern operating systems, especially when running large applications or performing intensive multitasking, often resulting in crashes and high latency. This research aims to quantitatively analyze the effectiveness of Virtual Memory (VM) implementation as a solution to this RAM constraint on the Windows 10 operating system, focusing on VM’s impact on CPU performance, GPU performance, and multitasking response. The methodology employed is a controlled experiment using industry-standard benchmarks: Cinebench R20 (CPU), Unigine Heaven (GPU), and response time measurements in intensive multitasking scenarios. Experimental results demonstrate that VM activation improves CPU/GPU performance by up to 5% and accelerates multitasking response time by up to 15%, confirming VM's effectiveness in mitigating memory bottlenecks. Nevertheless, this study also identifies potential performance overhead stemming from excessive paging and swapping processes, which trigger the phenomenon of Thrashing. Therefore, the research recommends a dual optimization strategy to achieve maximum and stable performance: software optimization via the Least Recently Used (LRU) algorithm to suppress page faults, supported by hardware optimization including the use of an SSD for the swap file and increased RAM capacity.

References

Aulia, W., Putri, S. H., & Emin, I. J. (2025). Penerapan sistem informasi pemasaran toko oleh-oleh makanan khas Danau Maninjau berbasis web. Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi, 3(3), 289–300. https://doi.org/10.61132/neptunus.v3i3.1035

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.

Gunawan, S. A., & Lestari, M. (2024). Analisis peran page fault dalam manajemen memori virtual untuk meningkatkan stabilitas aplikasi. Jurnal Teknik Elektro dan Komputer, 19(2), 70–85.

Hartono, E., & Kurniawan, A. (2025). Optimasi penggunaan sebagai swap file untuk mempercepat akses virtual memory pada Windows 10. Jurnal Teknologi Informasi dan Sains, 10(1), 1–15.

Hidayat, A. F. (2025). Efek fragmentasi ruang alamat pada implementasi virtual memory pada kernel Windows. Jurnal Riset Komputasi, 6(1), 30–45.

Kumar, R., Singh, A., & Kaur, G. (2020). Performance analysis of CPU and GPU under multitasking environment using Windows 10. International Journal of Computer Applications, 176(18), 15–21. https://doi.org/10.5120/ijca2020919876

Microsoft. (2023). Memory management and virtual memory in Windows 10. Microsoft Learn. https://learn.microsoft.com/en-us/windows-hardware/drivers/kernel/memory-management

Patel, D., & Sharma, M. (2021). Evaluation of virtual memory management impact on system performance. Journal of Computer Engineering and Technology, 12(4), 45–53. https://doi.org/10.1016/j.jcet.2021.04.005

Pratama, B. A. (2023). Pengukuran kecepatan respons aplikasi multitasking dengan variasi ukuran paging file pada sistem Windows. Jurnal Sistem Cerdas, 7(2), 120–135.

Rahmat, D., & Kusuma, W. (2023). Optimalisasi paging file pada Windows 10 untuk menanggulangi overhead swapping pada lingkungan komputasi berat. Jurnal Rekayasa Sistem Informasi, 14(1), 10–25.

Saputra, R. A., & Handayani, T. (2023). Perbandingan efektivitas algoritma paging (FIFO dan LRU) dalam mengelola overhead swapping pada sistem operasi. Jurnal Komputer dan Sistem Informasi, 15(3), 88–99.

Setyawan, D., & Amelia, R. (2024). Tinjauan konsep dan mekanisme kerja virtual memory: Paging dan swapping. Jurnal Ilmu Komputer dan Pendidikan, 11(3), 55–68.

Silberschatz, A., Galvin, P. B., & Gagne, G. (2020). Operating system concepts (10th ed.). John Wiley & Sons.

Simanjuntak, H., & Siregar, D. (2024). Analisis fenomena thrashing dan dampaknya pada kestabilan sistem operasi berbasis virtual memory. Jurnal Riset Teknik Elektro dan Informatika, 8(4), 210–225.

Wijaya, I. B., & Susanto, T. (2024). Pengujian pengaruh virtual memory terhadap kapasitas memori fisik dan performa dalam lingkungan Windows. Jurnal Informatika UPN Jatim, 12(1), 45–56.

Wijayanto, S. E., & Puspitasari, A. (2023). Studi komparatif kinerja sistem operasi Windows dengan dan tanpa pengaktifan virtual memory. Jurnal Sains dan Komputasi, 18(4), 180–195.

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Published

2025-10-29

How to Cite

Fauzia Fredella, & Ulya Rahman. (2025). Penerapan Virtual Memory terhadap Kinerja CPU, GPU, dan Respons Multitasking pada Windows 10. Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer, 3(5), 168–178. https://doi.org/10.61132/mars.v3i5.1133

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