Prasetyo, Yanuar (2022) Aplikasi Peramalan Diagnosa Penderita Covid-19 Menggunakan Metode Naive Bayes dengan Bahasa Pemrograman Php. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
This application for forecasting the diagnosis of COVID-19 sufferers aims to calculate how many patients die and live after being exposed to COVID-19 disease using the Naive Bayes method, based on the existing data set. The data is calculated using the Naive Bayes method and implemented in the php programming language. The background is made by continuing previous research which is the contents of the COVID-19 data set which is used as an application to predict that patients diagnosed with COVID-19 can be declared dead or alive. Naive Bayes is a classification method based on simple probability and is designed to be used with the assumption that between one class and another class are not interdependent. PHP programming stands for Hypertext Preprocessor which is a programming language that is widely used for handling the creation and development of a website and can be used in conjunction with HTML. The results obtained in this study used a black box test which has an accuracy of up to 100%. Using the Naive Bayes method with the php programming language which consists of training data and testing data. Keywords: Forecasting application, Covid 19, Naive bayes, PHP programming, Black box
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Yanuar Prasetyo | ||||||||||||
| Date Deposited: | 30 Jun 2022 05:16 | ||||||||||||
| Last Modified: | 30 Jun 2022 05:16 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/7259 |
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