Analisis Komparatif Performa Cloud Storage Pada ownCloud Infinite Scale (oCIS), Seafile, dan Google Drive

Prasetyo, Dhea Arfryza Ananda (2025) Analisis Komparatif Performa Cloud Storage Pada ownCloud Infinite Scale (oCIS), Seafile, dan Google Drive. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Teknologi cloud telah menjadi fondasi penting dalam mendukung transformasi digital di berbagai sektor. Salah satu pemanfaatan utamanya adalah layanan cloud storage, yang memungkinkan pengguna menyimpan, mengakses, dan berbagi data secara fleksibel. Penelitian ini bertujuan untuk melakukan analisis komparatif terhadap performa tiga platform cloud storage, yaitu Seafile, ownCloud Infinite Scale (oCIS), dan Google Drive. Pengujian dilakukan secara otomatis menggunakan skrip Python untuk mengukur parameter Quality of Service (QoS), meliputi throughput, delay, jitter, packet loss, serta penggunaan CPU dan RAM. Uji coba mencakup enam skenario file dengan ukuran ±100MB dan empat jenis operasi utama, yaitu upload, move, download, dan delete. Hasil menunjukkan bahwa oCIS memiliki performa terbaik dengan throughput tertinggi dan delay terendah, disusul oleh Seafile yang unggul dalam efisiensi penggunaan resource. Google Drive menunjukkan performa terendah, terutama dalam stabilitas jaringan. Dari sisi fitur, Google Drive unggul dalam kolaborasi, oCIS mendukung skalabilitas untuk kebutuhan institusi, sedangkan Seafile seimbang dari sisi fitur dan efisiensi. Selain itu, dari aspek biaya, oCIS merupakan pilihan paling ekonomis untuk institusi karena tidak memerlukan lisensi dan hanya membutuhkan biaya server, sedangkan Seafile Pro menawarkan biaya per pengguna yang relatif rendah. Google Drive memiliki biaya langganan tertinggi per pengguna, namun tidak membutuhkan infrastruktur teknis. Penelitian ini diharapkan menjadi referensi dalam memilih platform cloud storage yang sesuai kebutuhan, baik dari sisi performa, fitur, maupun efisiensi biaya.
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Cloud technology has become a vital foundation in supporting digital transformation across various sectors. One of its key applications is cloud storage services, which enable users to store, access, and share data flexibly. This study aims to conduct a comparative analysis of the performance of three cloud storage platforms: Seafile, ownCloud Infinite Scale (oCIS), and Google Drive. The testing process was automated using Python scripts to measure Quality of Service (QoS) parameters, including throughput, delay, jitter, packet loss, as well as CPU and RAM usage. The evaluation involved six file-based scenarios (±100MB each) and four main operations: upload, move, download, and delete. The results show that oCIS delivers the best performance with the highest throughput and lowest delay, followed by Seafile, which excels in resource usage efficiency. Google Drive exhibits the lowest performance, particularly in network stability. In terms of features, Google Drive is superior for collaboration, oCIS supports scalability for institutional needs, while Seafile offers a balance between functionality and efficiency. Additionally, in terms of cost, oCIS is the most economical option for institutions as it requires no licensing fees and only incurs server costs, whereas Seafile Pro offers relatively low per-user costs. Google Drive has the highest subscription fee per user but does not require any technical infrastructure. This study is expected to serve as a reference in selecting the most suitable cloud storage platform based on performance, features, and cost efficiency.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Cloud storage, delay, fitur, Google Drive, jitter, ownCloud Infinite Scale (oCIS), packet loss, performa , Quality of Service, Seafile, throughput
Subjects:	Q Science > QA Mathematics > QA76.585 Cloud computing. Mobile computing. T Technology > T Technology (General)
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis
Depositing User:	Dhea Arfryza Ananda Prasetyo
Date Deposited:	23 Jul 2025 03:52
Last Modified:	23 Jul 2025 03:52
URI:	http://repository.its.ac.id/id/eprint/120737

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