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Implementation of Fuzzy Inference System with Best-Worst Method for Cost Efficiency on Amazon Web Services

Journal of Advances in Information Systems and Technology · Vol. 4 No. 2 (2023) · hlm. 149–155

DOI
10.15294/jaist.v4i2.60569
ISSN
2715-999X, 2714-9714
Terbit
2023-03-10
Penerbit
Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

This study aims to reduce the cost of using computing services on AWS. Cost reduction is needed because there is a possibility that the total cost of using cloud services exceeds the estimated budget. One type of EC2 that offers a large discount is the Spot Instance. The downside of this type of EC2 is that AWS reserves the right to stop it at any time. The proposed solution is an automation system to select and run EC2 Spot Instance types based on price, discount, amount of memory, and vCPU usage from previous instances. The automation system is built with the implementation of fuzzy inference system and Best-Worst Method (BWM). All input data is obtained using the Boto3 SDK. System deployment is done in Lambda functions. This Lambda function is automatically executed whenever a Spot Instance is terminated by AWS. The EventBridge service will catch the event and then trigger the Lambda to run. System testing was run for 4 (four) days with event simulation using the Send Events feature. From these tests it is known that the automation system can select the appropriate instance and generate a total cost of $3.85 (USD). After calculating the total cost with regular EC2 estimation (On Demand), the cost is reduced by 71.28%. This number proved to be 4.28% greater than previous similar studies.

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  • State University of Semarang
  • Universitas Nahdlatul Ulama Blitar
  • Institut Teknologi Kalimantan
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Rekan penulisOrganisasiArtikel bersama
Muh. SholehAfiliasi tidak diketahui2
Martanto Setyo HusodoAfiliasi tidak diketahui2
Riza ArifudinState University of Semarang2
Deonisius Germandy Cahaya PutraAfiliasi tidak diketahui2
Vivi WulandariAfiliasi tidak diketahui2
Resta AdityatamaAfiliasi tidak diketahui2
Taripar Matius AlexanderAfiliasi tidak diketahui1
Florentina Yuni AriniState University of Semarang1
Athoillah AthoillahAfiliasi tidak diketahui1
Endang SugihartiState University of Semarang1
Kholiq BudimanAfiliasi tidak diketahui1
zaenal abidinAfiliasi tidak diketahui1
Alfath YanuartoAfiliasi tidak diketahui1
Dinar Diaz SeptianAfiliasi tidak diketahui1
Akhmad MunawarAfiliasi tidak diketahui1
Andika Enggal RamadhanAfiliasi tidak diketahui1
Bhekti KumorowatiAfiliasi tidak diketahui1
Sugianto SugiantoUniversitas Nahdlatul Ulama Blitar1
Cahya WulandariState University of Semarang1
Muhamad Sayuti HassanAfiliasi tidak diketahui1
Zidney Ilma Fazaada EmhaAfiliasi tidak diketahui1
Angel Novita SinuratAfiliasi tidak diketahui1
Tazkiyatun Aeni AmaliyahAfiliasi tidak diketahui1
Devi Tri WidyantiAfiliasi tidak diketahui1
Much Azis MuslimAfiliasi tidak diketahui1
Ahmad WarsunAfiliasi tidak diketahui1
Pradistia Edo KristiantoAfiliasi tidak diketahui1
Syehudin SyehudinAfiliasi tidak diketahui1
Alamsyah AlamsyahInstitut Teknologi Kalimantan1
Hendi SusantoAfiliasi tidak diketahui1
Adham Satria FirmansyahAfiliasi tidak diketahui1
Luthfi Ilham Agus PratamaAfiliasi tidak diketahui1
Muhammad Zaenal MuttaqinAfiliasi tidak diketahui1
Dian Tri WiyantiState University of Semarang1
Dante AlighiriState University of Semarang1
Priyantini WidiyaningrumAfiliasi tidak diketahui1
Agus YuliantoAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/jaist/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Implementation of Fuzzy Inference System with Best-Worst Method for Cost Efficiency on Amazon Web Services</dc:title>
	<dc:creator>Prastiwi, Annisya Dira</dc:creator>
	<dc:creator>Putra, Anggyi Trisnawan</dc:creator>
	<dc:description xml:lang="en-US">This study aims to reduce the cost of using computing services on AWS. Cost reduction is needed because there is a possibility that the total cost of using cloud services exceeds the estimated budget. One type of EC2 that offers a large discount is the Spot Instance. The downside of this type of EC2 is that AWS reserves the right to stop it at any time. The proposed solution is an automation system to select and run EC2 Spot Instance types based on price, discount, amount of memory, and vCPU usage from previous instances. The automation system is built with the implementation of fuzzy inference system and Best-Worst Method (BWM). All input data is obtained using the Boto3 SDK. System deployment is done in Lambda functions. This Lambda function is automatically executed whenever a Spot Instance is terminated by AWS. The EventBridge service will catch the event and then trigger the Lambda to run. System testing was run for 4 (four) days with event simulation using the Send Events feature. From these tests it is known that the automation system can select the appropriate instance and generate a total cost of $3.85 (USD). After calculating the total cost with regular EC2 estimation (On Demand), the cost is reduced by 71.28%. This number proved to be 4.28% greater than previous similar studies.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2023-03-10</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/jaist/article/view/60569</dc:identifier>
	<dc:identifier>10.15294/jaist.v4i2.60569</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Advances in Information Systems and Technology; Vol 4 No 2 (2022): October; 149-155</dc:source>
	<dc:source>2715-999X</dc:source>
	<dc:source>2714-9714</dc:source>
	<dc:source>10.15294/jaist.v4i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/jaist/article/view/60569/23885</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Journal of Advances in Information Systems and Technology</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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