Gabriela Calista Vania Putri, Ericson Saputera, Dorie Pandora Kesuma

Systematic Literature Review: Pemanfaatan Cloud Computing dalam Pengembangan Kecerdasan Buatan

Introduction

Systematic literature review: pemanfaatan cloud computing dalam pengembangan kecerdasan buatan. SLR pemanfaatan cloud computing dalam pengembangan AI. Temukan manfaat (skalabilitas, efisiensi) dan tantangan (keamanan, privasi), serta platform populer (Google Cloud, AWS, Azure).

Abstract

Cloud computing menyediakan sumber daya komputasi seperti penyimpanan, pemrosesan, dan jaringan melalui internet yang dapat diakses kapan saja. Model layanan cloud computing yang umum digunakan meliputi Infrastructure as a Service (IaaS), Platform as a Service (PaaS), dan Software as a Service (SaaS). Penelitian ini bertujuan untuk meninjau pemanfaatan cloud computing dalam pengembangan kecerdasan buatan (AI) dengan menggunakan pendekatan Systematic Literature Review (SLR). Artikel yang dianalisis dipublikasikan antara tahun 2019 hingga 2025 dan diperoleh dari dua basis data utama, yaitu Google Scholar dan Garuda Dikti. Dari 52 artikel yang ditemukan, sebanyak 40 artikel lolos seleksi berdasarkan kriteria inklusi dan eksklusi, dan 19 artikel dinyatakan relevan setelah melalui penilaian kualitas. Hasil analisis menunjukkan bahwa platform cloud yang paling sering digunakan dalam pengembangan AI adalah Google Cloud (36,8%), diikuti oleh AWS (26,3%) dan Microsoft Azure (21,1%). Pemanfaatan cloud computing dalam pengembangan AI memberikan berbagai manfaat seperti skalabilitas, efisiensi biaya, dan kemudahan akses terhadap layanan AI canggih. Namun, tantangan utama yang dihadapi meliputi isu keamanan dan privasi data, kompleksitas integrasi sistem, serta biaya operasional yang tidak terduga. Temuan ini menekankan pentingnya pengembangan strategi integrasi yang efektif untuk mengoptimalkan sinergi antara cloud computing dan kecerdasan buatan dalam konteks industri maupun penelitian di masa mendatang.

Review

This systematic literature review (SLR) offers a pertinent and well-structured examination of the utilization of cloud computing in artificial intelligence (AI) development. The paper clearly establishes its objective by defining cloud computing's core components and service models before focusing on its integration with AI. The chosen methodology, an SLR, is highly appropriate for comprehensively mapping the current state of this dynamic interdisciplinary field, drawing articles published between 2019 and 2025 from Google Scholar and Garuda Dikti. The meticulous selection process, from an initial 52 articles down to 19 relevant studies, underscores the rigorous approach taken to ensure the validity and reliability of the review's findings. The review effectively distills valuable insights regarding the contemporary landscape of cloud-AI integration. A key contribution is the clear identification of dominant cloud platforms in AI development, with Google Cloud, AWS, and Microsoft Azure being highlighted as the most frequently used choices, providing a practical benchmark for practitioners. Furthermore, the paper robustly articulates the significant benefits that cloud computing extends to AI initiatives, including enhanced scalability, improved cost efficiency, and facilitated access to advanced AI services. These findings collectively underscore the strategic advantages and transformative potential of cloud adoption in accelerating AI innovation and deployment. While comprehensive, the review also candidly addresses critical challenges inherent in the cloud-AI synergy. It highlights pressing concerns such as data security and privacy, the complexities of system integration, and the potential for unexpected operational costs, which are crucial considerations for future deployments. A potential minor limitation could be the exclusive reliance on two databases (Google Scholar and Garuda Dikti), which might potentially overlook some specialized publications. Nevertheless, the paper concludes with a forward-looking perspective, emphasizing the imperative for developing effective integration strategies to optimize the synergy between cloud computing and AI, thereby guiding future research and industrial applications towards more robust and secure advancements.

Full Text

Comments

You need to be logged in to post a comment.