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Lisnawati
Universitas Lambung Mangkurat
Computer Science & IT

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PENERAPAN METODE FUZZY NEUTROSOPHIC SOFT SETS UNTUK PREDIKSI STATUS PENGAWASAN COVID-19 Lisnawati; Andi Farmadi; Dwi Kartini; Mohammad Reza Faisal; Rudy Herteno
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Coronavirus Disease 2019 (COVID-19) is a new type of disease that has never been previously identified in humans and has been declared a pandemic. The diagnosis of the disease is complicated by the variety of symptoms and imaging findings and the severity of the disease at the time of presentation. Fuzzy Neutrosophic Soft Sets are able to handle many types of uncertainty data such as ambiguity, inaccuracy, ambiguity, and inconsistency. Therefore, Fuzzy Neutrosophic Soft Sets can be applied to overcome the uncertainty of symptoms in COVID-19 surveillance. This research was conducted by collecting and presenting the respondent's Neutrosophic value and Neutrosophic value as a knowledge base, then performed Fuzzy Neutrosophic Soft Sets operations (composition, complement, value function, and score function) to obtain the monitoring status of the predicted results. Furthermore, the monitoring status of the predicted results is compared with the actual monitoring status of the respondents to obtain the accuracy level of Fuzzy Neutrosophic Soft Sets. Based on testing of 12 respondents, with 7 respondents as training data and 5 respondents as testing data, the accuracy of the Fuzzy Neutrosophic Soft Sets method in the diagnosis of COVID-19 surveillance status was 80%.
Co-Authors Andi Farmadi Dwi Kartini Muhammad Reza Faisal, Muhammad Reza Rudy Herteno