KLASIFIKASI DIAGNOSA PENYAKIT LAMBUNG DENGAN MENGGUNAKAN METODE DESSICION TREE

MAULANI, ZESTY SYAH (2022) KLASIFIKASI DIAGNOSA PENYAKIT LAMBUNG DENGAN MENGGUNAKAN METODE DESSICION TREE. Skripsi thesis, UNIVERSITAS BHAYANGKARA SURABAYA.

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Abstract

Gastric disease, also known as heartburn, is caused by excess stomach acid, so that the stomach wall is not strong enough to hold the stomach acid for a long time, causing pain that is very disturbing to the patient. The classification of gastric disease diagnosis using the Dessicion Tree method is to determine gastric disease, so that with this web-based application, it is hoped that it will help the wider community as a user in finding information, consultation, or treatment for gastric disease in a clear, complete, fast and precise manner. Decision trees are used to model problems that consist of a series of decisions that lead to solutions. Each inner node represents a decision while the leaf represents a solution. Schema and decision tree structure is one of the modeling of the structure according to graph After the analysis, the system created has worked correctly according to the required design, namely the classification of gastric disease which will be used to diagnose gastric disease, the ID3 algorithm is used to calculate the overall data entrophy and then calculate the information gain of each criterion. Information gain from each criterion is obtained after calculating the entropy value of each criterion attribute

Item Type: Thesis (Skripsi)
Uncontrolled Keywords: stomach, ID3 algorithm, analysis
Subjects: 000 - COMPUTER SCIENCE, INFORMATIONS & GENERAL WORKS > 000 Computer science, information & general works > 003 Systems > 003.1 System Identification
000 - COMPUTER SCIENCE, INFORMATIONS & GENERAL WORKS > 000 Computer science, information & general works > 003 Systems > 003.1 System Identification
Divisions: Faculty of Engineering > Bachelor of Informations Technology
Depositing User: Perpus Ubhara Surabaya
Date Deposited: 21 Jan 2025 03:29
Last Modified: 21 Jan 2025 03:29
URI: http://eprints.ubhara.ac.id/id/eprint/2874

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