Decision Support System Determining Computer Virus Protection Applications Using Simple Additive Weighting (SAW) Method

Authors

  • Adi Widarma Universitas Asahan
  • M. Dedi Irawan Universitas Islam Negeri Sumatera Utara
  • Fajri Nurhidayahti Universitas Islam Negeri Sumatera Utara
  • Ranis Hsb Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.47709/cnahpc.v3i1.936

Keywords:

System, Protection, Virus, Computer, Simple Additive Weighting (SAW)

Abstract

The use of information technology devices such as computers or laptops is currently increasing. The increased use is due to the fact that these devices are very supportive of our daily work activities. With the increasing use of these computers, data security on a computer or laptop device must be completely safe from virus attacks. To ward off viral attacks m aka requires the application of anti-virus to inhibit and prevent a variety of viruses that enter into the computer system so that the computer user's activity was not bothered by the many viruses are easily spread. Because there are too many antiviruses on the market, it is necessary to choose a good antivirus. One of the ways to choose antivirus is the existence of a decision support system . In this study, the Simple Additive Weighting (SAW) method was applied for the anti-virus application selection system. This data assessment analysis aims to produce the best anti - virus application options that computer users can use to secure their computer data. The criteria and weights used are K1 = application rating (5%) , K2 = completeness of features (30%) , K3 = price / official license (5%) , K4 = malware detection (45%) and K5 = blocking URL (15%). Of the 25 alternatives used, the results of the study, namely alternative A1 = Kaspersky anti-virus get the highest ranking result.

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References

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Published

2021-03-02

How to Cite

Widarma, A., Dedi Irawan, M., Nurhidayahti , F. ., & Hsb, R. . (2021). Decision Support System Determining Computer Virus Protection Applications Using Simple Additive Weighting (SAW) Method. Journal of Computer Networks, Architecture and High Performance Computing, 3(1), 68–79. https://doi.org/10.47709/cnahpc.v3i1.936

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Source: OpenAlex  · Updated 2026-09-21 01:46 UTC