KOMPARASI ALGORITMA K-NEAREST NEIGHBOR DAN NAIVE BAIYES UNTUK MENDETEKSI DINI RESIKO KANKER SERVIKS PADA REMAJA

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Mayang Sari Yusri Ikhwani

Abstract

Cancer is now the most feared disease for everyone. There are many types of cancer that can be a killer for humans, one of which is cervical cancer. Cervical cancer has the highest number among the other deadliest cancers in Indonesia. Cervical cancer itself occurs because of the transmission of the HPV virus (human papillomavirus), but basically cervical cancer can be prevented early on by providing knowledge to the public, especially adolescents, so that it can reduce the incidence of cervical cancer.


Early detection is needed to prevent cervical cancer, there are several ways that can be done to detect early risk of cervical cancer in adolescents, one of them is by utilizing media technology. In this study the method used to predict the risk of cervical cancer in adolescents is done by comparing the two algorithms, K-Nearest Neighbor and Naïve Bayes, where each algorithm is tested to produce predictions with maximum accuracy.


Based on the results of the implementation and measurement of the two algorithms, the best algorithm is Naïve Bayes which is able to predict with an accuracy rate of 85.71 while K-Nearest Neighbor is able to predict with an accuracy of 80.95%. but this accuracy still cannot be considered excellent (very good) for that it is very necessary to develop further analysis and results, especially deepening the risk factors for cervical cancer in adolescents so that the results of more optimal accuracy can be obtained.

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References

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