Klasifikasi Penyakit Kanker Serviks Menggunakan Perbandingan Algoritma K-Nearest Neighbor dan Naïve Bayes
AbstractCervical cancer is cancer that grows on the cells in the cervix. Generally, cervical cancer shows no symptoms at an early stage. According to the Indonesian Doctors Association there are 600-750 women of reproductive age who die every month due to cervical cancer. One of the causes of cervical cancer is acute female smoking, sexual history and a lack of public knowledge of the symptoms of cervical cancer. To do an early check, an examination is carried out at the Puskesmas or Health Service Center first. This study uses the k-NN and Naive Bayes algorithms which will be compared first. Comparisons are made to get the best method of cervical cancer classification that will be used in the system. Therefore, this study will design a system that can diagnose cervical cancer patients using the best algorithm, based on general symptoms, more quickly and accurately in determining the prediction results. Keywords: Classification, Cervical Cancer, K-Nearest Neighbor, Naïve Bayes.
Copyright info for authors
1. Authors hold the copyright in any process, procedure, or article described in the work and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors retain publishing rights to re-use all or portion of the work in different work but can not granting third-party requests for reprinting and republishing the work.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.