ANALISIS KUALITAS DISASTER RECOVERY CENTER (DRC) DENGAN PARAMETER QUALITY OF SERVICES (QOS) MENGGUNAKAN METODE MANOVA

KASPARI, ANDRIAN and Heryanto, Ahmad and Hermansyah, Adi (2025) ANALISIS KUALITAS DISASTER RECOVERY CENTER (DRC) DENGAN PARAMETER QUALITY OF SERVICES (QOS) MENGGUNAKAN METODE MANOVA. Undergraduate thesis, Sriwijaya University.

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Abstract

Disaster Recovery Center (DRC) is an essential solution for maintaining the continuity of information technology services during disruptions. This study analyzes the quality of DRC using Quality of Service (QoS) parameters, namely throughput, delay, jitter, and packet loss, with the Multivariate Analysis of Variance (MANOVA) method. Implementation was done with a hot standby topology and testing of five scenarios, including normal conditions, high traffic load, and DoS attacks. Data was collected through network tapping and analyzed multivariately. The results show that DRC is able to maintain service reliability, with MANOVA identifying significant differences between scenarios and the best configuration. This method is effective for evaluating DRC performance and can serve as a reference for developing data recovery systems.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Disaster Recovery Center, QoS, MANOVA, Hot Standby
Subjects:	T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control) T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.6 General works Industrial engineering Information technology. Information systems (General) Management information systems -- Continued T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.64 Management of information systems Production capacity. Manufacturing capacity Cf. HD69.C3 Economics Cf. TS176+ Manufacturing engineering
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Andrian Kaspari
Date Deposited:	18 Sep 2025 07:39
Last Modified:	18 Sep 2025 07:39
URI:	http://repository.unsri.ac.id/id/eprint/184217

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