ANALISIS PREDIKSI PENYAKIT KANKER PARU-PARU MENGGUNAKAN NAIVE BAYES

• Main Author: Rafli Ramadhan, (Author)
• Format: Book
• Published: 2022-07-28.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata
• Notes: http://repository.upnvj.ac.id/20447/1/ABSTRAK.pdf; http://repository.upnvj.ac.id/20447/13/AWAL.pdf; http://repository.upnvj.ac.id/20447/3/BAB%20I.pdf; http://repository.upnvj.ac.id/20447/4/BAB%20II.pdf; http://repository.upnvj.ac.id/20447/5/BAB%20III.pdf; http://repository.upnvj.ac.id/20447/6/BAB%20IV.pdf; http://repository.upnvj.ac.id/20447/7/BAB%20V.pdf; http://repository.upnvj.ac.id/20447/8/DAFTAR%20PUSTAKA.pdf; http://repository.upnvj.ac.id/20447/9/RIWAYAT%20HIDUP.pdf; http://repository.upnvj.ac.id/20447/10/LAMPIRAN.pdf; http://repository.upnvj.ac.id/20447/11/HASIL%20PLAGIARISME.pdf; http://repository.upnvj.ac.id/20447/12/ARTIKEL%20KI.pdf
• Keywords: Q Science (General); QA75 Electronic computers. Computer science; R Medicine (General)

Nowadays, many people contract diseases such as cancer, even at a young age, many also experience it, although it is still dominated by the elderly. Lung cancer is one of the most common contributors to cancer in the world, there are at least 10-12% of cancer contributors from all existing cancers. With the development of technology that is increasingly advanced and rapid, people with cancer can be analyzed which will then be stored in a data about the characteristics of people with cancer. Naïve Bayes is one of the algorithms in determining predictions whether a person has lung cancer or not by determining from the existing characteristicsThere were at least 3 experiments by dividing the training data and test data with the details of the first experiment with 60% of the training data and 40% of the test data, the second experiment with 70% of the training data and 30% of the test data, and the third experiment with 80% of the training data and 20% of the test data. This test will run for approximately 3 to 4 months. The results of this study were for 60% of the training data and 40% of the test data resulted in an accuracy of 90.24% , and for 60% of the training data and 30% of the test data resulted in an accuracy of 83.87%, for 80% of the training data and 20% of the test data resulted in an accuracy of 87.10%.