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Image of PERBANDINGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR DALAM MENGKLASIFIKASI PENYAKIT JANTUNG

Skripsi

PERBANDINGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR DALAM MENGKLASIFIKASI PENYAKIT JANTUNG

Pratiwi, Mayti - Personal Name;

Penilaian

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Penilaian anda saat ini :  

Heart disease is the number one deadly disease in the world. However, most patients with heart disease do not know the initial symptoms that are felt and not a few people with coronary heart disease die due to a heart attack. This has prompted a lot of research on heart disease, one of which uses computer-based methods. This method is widely developed with the help of intelligent computing capable of processing large amounts of data. Processing large amounts of data can be done by classification using certain algorithms so that the results are fast and accurate. In this study, a comparison of the classification of heart disease was carried out using the Naïve Bayes and K-Nearest Neighbor methods. Tests were carried out with different percentages of data and the results obtained an average accuracy of 63,94%, precision 67,97%, Recall 68,81% and F-Measure 63,83% for Naïve Bayes. Meanwhile, for K-Nearest Neighbor, the average accuracy is 17,7%, precision is 14,34%, Recall is 8,14% and F-Measure is 9,54%.


Availability
Inventory Code Barcode Call Number Location Status
2107004065T58610T586102021Central Library (2107004065)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T586102021
Publisher
Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021
Collation
xv, 75 hlm,: ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.07
Content Type
Text
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Pemrosesan data
Prodi Teknik Informatika
Specific Detail Info
-
Statement of Responsibility
MURZ
Other version/related

No other version available

File Attachment
  • PERBANDINGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR DALAM MENGKLASIFIKASI PENYAKIT JANTUNG
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