{"title":"深度学习和MOORA性能方法在多准则决策中的比较——以最佳公共卫生中心为例","authors":"None Rizki Anantama, None Rachmad Hidayat","doi":"10.47577/technium.v17i.10093","DOIUrl":null,"url":null,"abstract":"This research paper compares the performance of the deep learning and MOORA methods in making multi-criteria decisions to choose the best puskesmas. This paper discusses the methodologies used in both approaches, the architectures and equations used in deep learning, and the advantages and limitations of each method. The results show that the deep learning approach achieves 100% accuracy and the MOORA approach dss model obtains an accuracy of 95.75%.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Deep Learning and MOORA Performance Methods in Multi Criteria Decision Making with Case Studies Best public health center\",\"authors\":\"None Rizki Anantama, None Rachmad Hidayat\",\"doi\":\"10.47577/technium.v17i.10093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research paper compares the performance of the deep learning and MOORA methods in making multi-criteria decisions to choose the best puskesmas. This paper discusses the methodologies used in both approaches, the architectures and equations used in deep learning, and the advantages and limitations of each method. The results show that the deep learning approach achieves 100% accuracy and the MOORA approach dss model obtains an accuracy of 95.75%.\",\"PeriodicalId\":490649,\"journal\":{\"name\":\"Technium\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47577/technium.v17i.10093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47577/technium.v17i.10093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Deep Learning and MOORA Performance Methods in Multi Criteria Decision Making with Case Studies Best public health center
This research paper compares the performance of the deep learning and MOORA methods in making multi-criteria decisions to choose the best puskesmas. This paper discusses the methodologies used in both approaches, the architectures and equations used in deep learning, and the advantages and limitations of each method. The results show that the deep learning approach achieves 100% accuracy and the MOORA approach dss model obtains an accuracy of 95.75%.
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