KOMBINASI METODE FUZZY LOGIC DAN NAIVE BAYES DALAM MENDIAGNOSA PENYAKIT DIABETES MELITUS

SATRIA, DITO BAYU and Efendi, Rusdi and Miraswan, Kanda Januar (2020) KOMBINASI METODE FUZZY LOGIC DAN NAIVE BAYES DALAM MENDIAGNOSA PENYAKIT DIABETES MELITUS. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_09021181520024.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy
	Text RAMA_55201_09021181520024_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (13MB) | Request a copy
Preview	Text RAMA_55201_09021181520024_8826630017_0009019002_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (576kB) | Preview
	Text RAMA_55201_09021181520024_8826630017_0009019002_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (825kB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (838kB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (318kB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (88kB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (296kB) | Request a copy
	Text RAMA_55201_09021181520024_8826630017_0009019002_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy

Abstract

Diabetes mellitus is a chronic metabolic disorder due to the pancreas not producing enough insulin or unable to use insulin produced effectively. This disease is characterized by high glucose levels. Diabetes mellitus is also known as the silent killer, because it is often not realized by the sufferer and when it is known that various complications have occurred. Base on these problems, a system that can help diagnose diabetes mellitus quickly and accurately is needed. In this research, an expert system was developed that can help diagnose diabetes mellitus by using combination of Fuzzy Logic and Naïve Bayes methods. Naïve Bayes method is a classification that uses probability and statistical methods. Naïve Bayes was choosen because this method works better compared to other classifier models. In its calculation, the Naïve Bayes method will be assisted by the Fuzzy Logic method to overcome fuzzy values. The total amount of data tested amounted to 30 data. The accuracy of the test results reached 93.3%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sistem Pakar, Fuzzy Logic, Naive Bayes, Diabetes Melitus
Subjects:	Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 6817 not found.
Date Deposited:	03 Aug 2020 06:09
Last Modified:	03 Aug 2020 06:09
URI:	http://repository.unsri.ac.id/id/eprint/32012

Actions (login required)

View Item