Analisis Trade-Off Konsumsi Energi dalam Adopsi Cloud Computing: Perspektif Green IT dan Keberlanjutan Infrastruktur Digital

 Mhd Juanda Harahap

Abstract


Cloud computing has become an essential infrastructure for digital transformation across various sectors. Its ability to provide flexible, scalable, and on-demand computing resources offers organizations opportunities to improve operational efficiency. However, the rapid growth of cloud services has also increased concerns regarding energy consumption and environmental sustainability. This study aims to analyze energy-consumption trade-offs in cloud computing adoption from the perspective of Green Information Technology (Green IT). The research employed a qualitative literature review by examining studies related to green cloud computing, sustainable data centers, energy efficiency, digital systems, and computing-resource management. The analysis focuses on infrastructure consolidation, virtualization, data-center energy consumption, computing workloads, and the environmental consequences of digital transformation. The findings indicate that cloud computing can improve resource utilization through infrastructure consolidation and dynamic resource allocation. Nevertheless, efficiency gains at the organizational level do not necessarily produce proportional reductions in total energy consumption because computing demand may increase as digital services become more accessible. The environmental benefits of cloud adoption therefore depend on workload management, infrastructure efficiency, data-center operations, and organizational technology policies. This study concludes that cloud computing should not automatically be categorized as environmentally sustainable; instead, its contribution to Green IT depends on comprehensive energy management throughout the digital infrastructure lifecycle.

Keywords


Artificial Intelligence, Mahasiswa IT, Kesiapan Kompetensi, Disrupsi Pekerjaan, Persepsi.

Full Text:

PDF

References


P. Hatta, Hadiyanto, and C. W. Budiyanto, “A Systematic Literature Review of Sustainable Cloud Computing Adoption in Higher Education Institutions Covering Architectures, Critical Factors, and Green IT Practices,” Discover Computing, vol. 29, Art. no. 266, 2026, doi: 10.1007/s10791-026-10160-7.

D. Biswas, S. Jahan, S. Saha, and M. Samsuddoha, “A Succinct State-of-the-Art Survey on Green Cloud Computing: Challenges, Strategies, and Future Directions,” Sustainable Computing: Informatics and Systems, vol. 44, Art. no. 101036, 2024, doi: 10.1016/j.suscom.2024.101036.

R. Buyya, S. Ilager, and P. Arroba, “Energy-Efficiency and Sustainability in New Generation Cloud Computing: A Vision and Directions for Integrated Management of Data Centre Resources and Workloads,” Software: Practice and Experience, vol. 54, no. 1, pp. 24–38, 2024.

“A Systematic Review of Green-Aware Management Techniques for Sustainable Data Center,” Sustainable Computing: Informatics and Systems, vol. 42, Art. no. 100989, 2024, doi: 10.1016/j.suscom.2024.100989.

P. K. Singh, S. Misra, S. Mittal, and S. Kumar, “Green Cloud Computing and Energy Efficiency: A Systematic Literature Review and Research Agenda,” 2024.

M. Masri, M. I. Abas, W. Hasyim, and I. Ibrahim, “Sistem Inventarisasi Aset Universitas Muhammadiyah Gorontalo Berbasis Web,” Jurnal Ilmu Komputer (JUIK), vol. 2, no. 2, pp. 27–30, 2022, doi: 10.31314/juik.v2i2.1712.

S. Yusuf, M. I. Abas, S. Syahrial, and R. Lamusu, “Penerapan Model Unified Theory of Acceptance and Use of Technology (UTAUT) terhadap Penggunaan Sistem Informasi Akademik Universitas Muhammadiyah Gorontalo,” Jurnal Ilmu Komputer (JUIK), vol. 2, no. 2, pp. 31–36, 2022, doi: 10.31314/juik.v2i2.1714.

T. P. Handayani and M. I. Abas, “Comparative Analysis of CNN-LSTM and LSTM Models for Cyberbullying Detection with Increasing Dataset Sizes,” Jurnal Ilmu Komputer (JUIK), vol. 4, no. 2, pp. 75–85, 2024, doi: 10.31314/juik.v4i2.3185.

B. I. Mahendra, M. I. Abas, S. Syahrial, and W. E. Pranata, “Rancang Bangun Pengaturan Pakan Ikan Nila Berbasis Internet of Things,” Jurnal Ilmu Komputer (JUIK), vol. 5, no. 1, pp. 20–35, 2025, doi: 10.31314/juik.v5i1.3899.

W. E. Pranata, M. I. Abas, I. Ibrahim, R. Lamusu, and S. Syahrial, “Konstruksi Algoritma Pewarnaan Titik Pelangi pada Graf Pohon,” Jurnal Ilmu Komputer (JUIK), vol. 5, no. 1, pp. 13–19, 2025, doi: 10.31314/juik.v5i1.3839.

R. Antupetu, M. I. Abas, A. Lasarudin, and R. Lamusu, “Digital Library Universitas Muhammadiyah Gorontalo,” Jurnal Ilmu Komputer (JUIK), vol. 4, no. 1, pp. 1–15, 2024, doi: 10.31314/juik.v4i1.2797.

N. K. Sulistyawati, W. Hasyim, R. Maku, and M. I. Abas, “Analisis Tingkat Kepuasan Pengguna Sistem Informasi Elektronik Kinerja ASN (SI-EKA) di Kementerian Agama Menggunakan Metode WebQual,” Jurnal Ilmu Komputer (JUIK), vol. 4, no. 1, pp. 28–39, 2024, doi: 10.31314/juik.v4i1.2804.

M. A. Chandra, I. Isminarti, F. Fauziah, Y. B. Mulyadi, and M. I. Abas, “Optimizing Production Process by Integrating 3D Manufacturing Technology Using Autodesk Inventor Software to Improve Efficiency,” Jurnal Ilmu Komputer (JUIK), 2024.

F. Adisyar, M. I. Abas, W. E. Pranata, R. Lamusu, S. Syahrial, and I. Ibrahim, “Apple Fruit Quality Detection (Good and Rotten) Using the YOLOv5 Method,” Jurnal Ilmu Komputer (JUIK), vol. 6, no. 1, pp. 24–31, 2026, doi: 10.31314/juik.v6i1.5539.

N. M. Tangahu, M. I. Abas, W. E. Pranata, R. Lamusu, S. Syahrial, and I. Ibrahim, “Avocado Ripeness Classification Using a Convolutional Neural Network (CNN),” Jurnal Ilmu Komputer (JUIK), vol. 6, no. 1, pp. 32–38, 2026, doi: 10.31314/juik.v6i1.5540.


DOI: http://dx.doi.org/10.31314/juik.v6i2.5687

Article metrics

Abstract views : 15 | views : 2

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Jurnal Ilmu Komputer (JUIK)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.