Analisis Perbandingan Performa Virtualisasi Server Sebagai Basis Layanan Infrastructure As A Service Pada Jaringan Cloud
DOI:
https://doi.org/10.30812/matrik.v19i1.433Keywords:
Infrastructure as a Service, Proxmox, VMWare ESXi, XenServer, Action ResearchAbstract
Cloud Computing provides convenience and comfort to every service. Infrastructure as a Service is one of the cloud computing services that is a choice of several users, it is very important to know the performance of each existing platform in order to get the maximum result according to our needs. In this study, testing 3 platforms of cloud computing service providers are VMWare ESXi, XenServer, and Proxmox, using action research methods. From the results of performance measurements, then analyzed and compared with the minimum and maximum limits. The tested indicators are response time, throughput, and resource-utilization as a comparison of server virtualization performance implementations. In the resource utilization testing when the condition of installing an operating system, CPU usage on the Proxmox platform shows the lowest usage of 10.72%, and the lowest RAM usage of 53.32% also on the Proxmox platform. In the resource test utilization when idle state shows the lowest usage of 5.78% on the Proxmox platform, while the lowest RAM usage is 57.25% on the VMWare ESXi platform. The mean resource utilization tests indicate that the Proxmox platform is better. At the throughput test when the upload measurement of the XenServer platform is better 1.37 MB/s, while the throughput test when the download of the VMWare ESXi platform is better than 1.39 MB/s. On response time testing shows the platform VMWare ESXi as the fastest is 0.180 sec.
Downloads
Downloads
Published
Issue
Section
How to Cite
Similar Articles
- Anugerah Bagus Wijaya, Suliswaningsih Suliswaningsih, Argiyan Dwi Pritama, Meningkatkan Rasa Nasionalisme Siswa Melalui Game Base Learning , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 1 (2019)
- William Barkem, Jeckson Sidabutar, Digital Forensic Analysis of WhatsApp Business Applications on Android-Based Smartphones Using NIST , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Firman Noor Hasan, Achmad Sufyan Aziz, Yos Nofendri, Utilization of Data Mining on MSMEs using FP-Growth Algorithm for Menu Recommendations , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Moh.Erwin Indrawan, Ahmat Adil, IMPLEMENTASI RESTFUL WEB SERVICE ONE CHIP MULTI-CLIENT UNTUK MENGOPTIMALKAN PENJUALAN PULSA ALL OPERATOR , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 15 No. 2 (2016)
- Dadang Priyanto, Bambang Krismono Triwijoyo, Deny Jollyta, Hairani Hairani, Ni Gusti Ayu Dasriani, Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Anas Syaifudin, Purwanto Purwanto, Heribertus Himawan, M. Arief Soeleman, Customer Segmentation with RFM Model using Fuzzy C-Means and Genetic Programming , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Rahman Rahman, Teguh Iman Hermanto, Meriska Defriani, Hyperparamaters Fine Tuning for Bidirectional Long Short Term Memory on Food Delivery , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 1 (2023)
- Viva Arifin, Velia Handayani, Luh Kesuma Wardhani, Hendra Bayu Suseno, Siti Ummi Masruroh, User Interface and Exprience Gamification-Based E-Learning with Design Science Research Methodology , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 1 (2022)
- Jelita Asian, Dimas Erlangga, Media Ayu, Data Exfiltration Anomaly Detection on Enterprise Networks using Deep Packet Inspection , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Budi Sumanto, Salima Nurrahma, Comparison of Random Forest Support Vector Machine and Passive Aggressive Models on E-nose-Based Aromatic Rice Classification , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 3 (2025)
You may also start an advanced similarity search for this article.
.png)











