Meina Noor Triana, . (2022) Sistem Pakar Untuk Mendiagnosa Tipe Gejala Covid-19 Menggunakan Metode Dempster Shafer. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
In this study, an expert system was designed to solve the problem, namely making a diagnosis of Covid-19 symptoms with the appearance of the symptoms experienced to determining the type of Covid-19 symptoms experienced by the user. In designing the expert system, the Dempster Shafer method is used as a calculation of the value/degree of confidence based on the symptoms experienced by the user. Dempster Shafer is a collection of uncertainty, Interval [belief, plausibility] describes the Dempster Shafer method, where trust is a measure of evidence (symptoms) to support a proposition. If 0, it is determined that there is no evidence value. If feasible, namely the certainty of the symptoms. In this study, the system outputs an initial diagnosis of the type of symptoms experienced by the user and about how to treat it. The purpose of this expert system is to help users find out the type of Covid-19 symptoms they are experiencing as well as information about how to treat them before taking further action. This study uses the HTML, PHP, and CSS programming languages, as well as the dempster shafer method to calculate the symptom confidence value experienced by people who have been questioned about Covid-19 and uses black box testing to ensure that the system works as expected without any errors. Based on the accuracy of the dempster shafer method system has an accuracy value of 79.93%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810511003] [Pembimbing 1: Yuni Widiastiwi] [Pembimbing 2: Ria Astriratma] [Penguji 1: Ermatita] [Penguji 2: Nurul Chamidah] |
| Uncontrolled Keywords: | Symptom Covid-19, Symptom Type Covid-19, Dempster Shafer, Expert System, Black Box |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Meina Noor Triana |
| Date Deposited: | 12 Aug 2022 02:16 |
| Last Modified: | 12 Aug 2022 02:16 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19671 |
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