KLASIFIKASI PENDERITA PENYAKIT DEMAM BERDARAH DENGUE (DBD) DENGAN METODE NAIVE BAYES

AMELIA, SUCI and Rini, Dian Palupi and Satria, Hadipurnawan (2022) KLASIFIKASI PENDERITA PENYAKIT DEMAM BERDARAH DENGUE (DBD) DENGAN METODE NAIVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

Dengue Hemorrhagic Fever (DHF) is a disease caused by infected mosquitoes, especially Aedes albopictus and Aedes aegypti mosquitoes. Dengue hemorrhagic fever is included in the category of dangerous diseases that can cause death. The length of time to know the results of the diagnosis of the disease is an obstacle for sufferers of dengue hemorrhagic fever to be given further treatment. This research was conducted to speed up knowing the results of the diagnosis using the Naïve Bayes method. Classification with Naïve Bayes is done by calculating the class probability value for each attribute. This study was conducted to obtain classification results with a high degree of accuracy and provide a diagnosis of dengue hemorrhagic fever (DHF) patients. From the results of the classification using split validation, it produces the highest accuracy value of 88.89% which is included in the excellent classification.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Naive Bayes , Data Mining , Dengue Hemorrhagic Fever
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Suci Amelia
Date Deposited:	12 Jan 2023 07:56
Last Modified:	12 Jan 2023 07:56
URI:	http://repository.unsri.ac.id/id/eprint/85905

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