CD Skripsi

Deteksi Komentar Spam Pada Media Sosial Instagram Menggunakan Metode Naïve Bayes

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ABSTRACT
Text 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%.

Keywords : Instagram, Spam Comments, Naïve Bayes Classifier, Text Mining.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 05.119 (0010)

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Sistem Informasi., 2018

Deskripsi Fisik

xiv, 58 hlm.: ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 05.119 (0010)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

JAKA

Versi lain/terkait

Lampiran Berkas

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