DETEKSI KOMENTAR SPAM PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE NAÏVE BAYES

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dc.contributor.authorAndriani, Sela
dc.contributor.authorSalambue, Roni
dc.date.accessioned2019-01-31T03:13:01Z
dc.date.available2019-01-31T03:13:01Z
dc.date.issued2019-01-31
dc.description.abstractText Mining is the process of finding new information or trends that were previously not revealed by processing and analyzing large amounts of data. In this thesis text mining is used to classify comments on Instagram social media. This technique aims to distinguish spam and not spam comments. One of the algorithms used in the classification is Naïve Bayes Classifier (NBC). In the NBC method, there are two stages, they are Training stage and the Testing Phase. Before the classification is done first the data will go through the Preprocessing stage, in which there are casefolding, stopcharacter removal, stopword, stemming and weighting. Evaluation to measure accuracy using Confussion Matrix which produces 93% Accuracy, 92% Precision, Recall 93.87% and Error Rate 7%.en_US
dc.description.sponsorshipJurusan Ilmu Komputer Fakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttp://repository.unri.ac.id/handle/123456789/9601
dc.language.isoenen_US
dc.publisherwahyu sari yenien_US
dc.subjectInstagramen_US
dc.subjectSpam Commentsen_US
dc.subjectNaïve Bayes Classifieren_US
dc.subjectText Miningen_US
dc.titleDETEKSI KOMENTAR SPAM PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE NAÏVE BAYESen_US
dc.typeArticleen_US

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