Klasifikasi kanker paru dengan menggunakan algoritma classify by sequence (CBS)

Sukadiana, I Putu Eddy (2015) Klasifikasi kanker paru dengan menggunakan algoritma classify by sequence (CBS). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kanker paru-paru merupakan penyakit dengan ciri khas adanya pertumbuhan sel yang tidak terkontrol pada jaringan paru-paru. Salah satu pendekatan (metode) untuk mengidentifikasi kanker paru adalah pendekatan data mining. Beberapa teknik data mining telah banyak dikembangkan seperti teknik asosiasi, clustering, sequence pattern dan klasifikasi. Berkembang pula metode klasifikasi dengan penggabungan sequential pattern mining dan induksi probabiltas yang dikenal sebagai algoritma Classify-by-Sequence (CBS). Belum ada kajian yang dilakukan mengenai data mining untuk data rekam medis dengan memanfaatkan algoritma Classify-by-Sequence (CBS). Pada penelitian ini akan dilakukan klasifikasi data rekam medis pada Rumah Sakit Umum Daerah (RSUD) di Denpasar, Bali,yang diolah dengan menggunakan Matlab R2009a. Diharapkan pada penelitian ini akan menunjukkan hasil akurasi yang tinggi meskipun hanya menggunakan dataset yang kecil. =========================================================================================== Lungs cancer is a diseases that has a characteristic of abnormal sel growth in the lungs. One of the method use to identify cancer is the data mining. A few technique for data mining had been developed, such as association, clustering, sequence pattern and classification. Other method for classification also been developed, wich combine the sequential pattern mining with probability induction known as Classify by Sequence. There aren’t any research that have been done about data mining for medical record that using Classify by Sequence algorithm. This research will classify the patient medical records in regional public hospital in Denpasar, Bali, that will be process in Matlab R2009a. hopefully on this research will show high accuracy value, despite using small dataset.

Item Type: Thesis (Undergraduate)
Additional Information: RSMa 515.24 Suk k
Uncontrolled Keywords: Data mining, Classify by Sequence, Medical record, Lung cancer, CBS, Rekam medis, Kanker paru
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions: Faculty of Mathematics and Science > Mathematics > (S1) Undergraduate Theses
Depositing User: Eny Widiastuti -
Date Deposited: 06 Apr 2018 04:10
Last Modified: 06 Apr 2018 04:10
URI: http://repository.its.ac.id/id/eprint/51704

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