IMPLEMENTASI ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI KOMENTAR SPAM PADA INSTAGRAM

Beta Priyoko, Ainul Yaqin
UNIVERSITAS AMIKOM YOGYAKARTA.2019

A B S T R A C T

Instagram is one of the most popular social media in Indonesia. With instagram, users can share their moments of life in the form of photos or videos. Instagram users can follow each other. But when a user already has a lot of followers, many instagram accounts also respond to posts with comments that can be categorized as spam.

Spam comments are usually found in every account post that has a lot of followers, especially public figures in Indonesia and of course this is very annoying. Instagram has provided services to delete or hide comments, but a model is still needed to detect comments that are spam or notspam.The Naive Bayes algorithm will look for the probability of each class when the comments are inputed. Before the comments probability are calculated for each class, comments will be processed through the preprocessing stage, namely casefolding, cleaning, tokenizing, and stemming.

After knowing the probability value of each class, then the probability value will be compared. If the highest probability value is a comment that is hypothesized as spam class, then the comment will be labeled as spam. If the highest probability value is a comment that is hypothesized as notspam class, then the comment will be labeled as notspam.Model evaluation measures showed good results: precision of 0.72, recall of 0.98 and F1-measure of 0.83, therefore spam comments classification using Naive Bayes can be considered as successful.

Keywords - Naive Bayes, Bayesian, Text Classification, Preprocessing, Instagram.

CategoryUndergraduate Thesis
Posted Date30 Maret 2019
Modified Date30 Maret 2019
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