Penerapan Teknologi Cloning Menggunakan Software Acronis untuk Optimalisasi Proses Instalasi Ulang Sistem Operasi Windows di Laboratorium Data Mining
Contributors
Bayu Hertanta
Keywords
Proceeding
Track
General Track
License
Copyright (c) 2025 Seminar Nasional Hasil Penelitian dan Pengabdian Masyarakat (SemnasPPM)

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abstract
Computer laboratories play a vital role in supporting learning activities, particularly in practical sessions that involve a large number of students and computers. One of the main challenges faced is the need to reinstall the operating system when errors or failures occur. Manual installation requires an average of more than 50 minutes per computer, which is highly inefficient on a large scale. This study aims to evaluate the implementation of cloning technology using Acronis software as a more efficient alternative, by comparing the manual method and the cloning method in reinstalling Windows operating systems at the Data Mining Laboratory, Universitas Islam Indonesia. The research employed a quantitative approach by collecting installation time data from five computers as samples, followed by statistical analysis using a paired t-test in R software, as well as an estimation for 50 computers. The results show that the cloning method required approximately 15 minutes per computer, while the manual method took around 52 minutes per computer. The statistical test produced a p-value of 0.1333 (> 0.05), indicating no significant difference at the 95% confidence level. Nevertheless, descriptive analysis revealed that cloning was on average 24 minutes faster than the manual method. The estimation for 50 computers demonstrated a total installation time of 1398.66 minutes with cloning and 2608.15 minutes with the manual method, resulting in a time saving of more than 1200 minutes (±20 hours). Therefore, the implementation of Acronis cloning technology can be considered more efficient and feasible to optimize computer laboratory management.