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All Journal STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Fikry Ramadhana
Universitas Nasional
Computer Science & IT Mathematics

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Aplikasi Sistem Pakar untuk Mendiagnosa Penyakit ISPA menggunakan Metode Naive Bayes Berbasis Website Fikry Ramadhana; Fauziah Fauziah; Winarsih Winarsih
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 4, No 3 (2020)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.306 KB) | DOI: 10.30998/string.v4i3.5441

Abstract

ISPA (Acute Respiratory Infection) is a disease that occurs due to respiratory tract disorders that can cause a variety of diseases ranging from asymptomatic illnesses, mild to severe infections due to environmental factors. The lack of public knowledge about the symptoms, how to treat it and how to overcome it result in a fairly high mortality rate due to ISPA. The expert system to be created is intended to make it easier a person to diagnose ISPA by adopting human knowledge into a computer system so the expert system is able to solve problems like an expert does. Expert system application  is made using the Naive Bayesmethod because the Naive Bayesmethod is the best classification method with high probability when used in its system calculation. With this application, people will feel like they are consulting with a doctor or an expert who handles ISPA. This application is built based on websites that use the PHP programming language, Codeigniter framework and MySQL database. There are 104 training data and 39 testing data that have been tested. From 39 tests, there are 36 test data that are suitable and there are 3 test data that are not suitable. Accuracy obtained from the test is of 92.3%.
Co-Authors Fauziah Fauziah Winarsih Winarsih