Implementasi Metode Dempster-Shafer Pada Sistem Pakar Diagnosa Penyakit Tumor Mediastinum Pada Manusia Berbasis Web

  • Ipandi Siburian * Mail Siburian, Indonesia
Keywords: Expert System; Mediastinum Tumor Disease; Dempster-Shafer Method

Abstract

Artificial intelligence (Artificial Intelligence) is a system that adopts knowledge from experts into an expert system, so that the computer can do as it is done by experts (experts) who act and can assist in providing solutions and making knowledge-based decisions appropriately. Expert systems are computer-based systems that use knowledge, facts, and reasoning techniques in solving problems, and usually can only be solved by an expert in a particular field. The expert system adds value to technology to help doctors diagnose diseases and provide information about the types of diseases, as well as general symptoms of mediastinal tumors.Mediastinum tumors are tumors found in the mediastinum, namely the imaginary cavity between the left and right lungs, the mediastinum contains the heart, large blood vessels, trachea, thymus, lymph nodes and connective tissue. The mediastinum is an important part of the thorax which is located between the pleuralist cavita and contains many important organs and vital structures. The mediastinum is divided into 4 chambers, namely anterior (front), middle, and posterior (back) superior and medial. Implementing the dempster-shafer method in the expert system it aims to diagnose web-based mediastinal tumor in humans based on the symptoms of mediastinal tumor. From the results of this study, it can be concluded that the expert system of diagnosing mediastinal tumors in humans is expected to help doctors (experts) in providing accurate and accurate diagnosis, so that patients know what disease they are suffering from.

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Bulletin of Information Technology (BIT)
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Published
2020-01-10
How to Cite
Siburian, I. (2020). Implementasi Metode Dempster-Shafer Pada Sistem Pakar Diagnosa Penyakit Tumor Mediastinum Pada Manusia Berbasis Web. Bulletin of Information Technology (BIT), 1(1), 1 - 8. Retrieved from https://journal.fkpt.org/index.php/BIT/article/view/1
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Vol 1 No 1: Maret 2020
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Articles

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