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dc.contributor.authorBudiman, Edy
dc.date.accessioned2021-02-18T09:41:55Z
dc.date.available2021-02-18T09:41:55Z
dc.date.issued2020-10-23
dc.identifier.citationBudiman, E. (2020). Importance-weighted Ranking Methods for Preference the Covid-19 Pandemic Social Assistance. International Journal of Engineering and Advanced Technology (IJEAT), 10(1), 108–115. https://doi.org/10.35940/ijeat.A1743.1010120en_US
dc.identifier.other1345680959
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/5791
dc.description.abstractIssues importance-weighted value is a critical aspect of decision making. Differences in weight, even the slightest change in weight assignment, can drastically change the final decision. Moreover, in the case of distributing social assistance during the Covid-19 pandemic, objectivity and accuracy of weighting the criteria for potential recipients are very important applied for the welfare of the community. The proposes study 3 popular models of ranking methods for weighting criteria in the internet data package assistance cases. Weighting is given to 390 alternatives with 5 decision-making criteria based on online learning needs and economic cost capabilities. The decision analysis method uses the reference point and optimization from Moora. The study results were found accuracy, precision and error rate performance each method using a confusion matrix approach. The study results discussed raised several important points of findings, that the three ranking methods (RS, RR, ROD) have their respective characteristics in weighting importance, where the level of accuracy and precision of the rank-sum method is better than the RR and ROD methods (for the case: 5 criteria; 390 alternatives). Other things in giving weight value from important to most important are comparable, and the weight value of the non-benefit (cost) criteria in the ranking method have a significant effect on performance results. These three methods are simple in use and with the assessment of replacement weights that can be determined how important these variables are to the principal of these criteria.en_US
dc.language.isoenen_US
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publication (BEIESP)en_US
dc.relation.ispartofseries;1345680959
dc.subjectweightingen_US
dc.subjectrank methoden_US
dc.subjectmcdmen_US
dc.subjectsocoal assistanceen_US
dc.titleTurnitin : Importance-weighted Ranking Methods for Preference the Covid-19 Pandemic Social Assistanceen_US
dc.typeArticleen_US


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