KLASIFIKASI KOMENTAR SPAM PADA YOUTUBE MENGGUNAKAN METODE NAÏVE BAYES, SUPPORT VECTOR MACHINE, DAN K-NEAREST NEIGHBORS

. Burhanudin, Yunarti Musa'adah, Yaya Wihardi

Abstract


Social mediabecome popular in this day. Sharing the daily moments in social media has become a daily routine. People can also discuss about the post in the existing comment field. For example a comment on Youtube video. But the popularity of social media bring some problems with attracting users who spread spam content on comments. In this research, will be discussed about the classification of spam comments on Youtube with several methods tested. The dataset contains 1956 data,that used to train data. The result of model evaluation using cross validation resulted Support Vector Machine method with Linear approach has highest accuracy equal to 91,92%. Expectedby this research can provide solutions as an effort to prevent spam content in social media comment field..

Keywords


knn; naive bayes; svm

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References


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DOI: http://dx.doi.org/10.26798/jiko.v3i2.139

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Copyright (c) 2018 . Burhanudin, Yunarti Musa'adah, Yaya Wihardi


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