Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 10 (2018): Oktober 2018

Implementasi Metode Backpropagation Neural Network Berbasis Lexicon Based Features dan Bag Of Words untuk Identifikasi Ujaran Kebencian pada Twitter

Muhammad Mishbahul Munir (Fakultas Ilmu Komputer, Universitas Brawijaya)
Mochamad Ali Fauzi (Fakultas Ilmu Komputer, Universitas Brawijaya)
Rizal Setya Perdana (Fakultas Ilmu Komputer, Universitas Brawijaya)



Article Info

Publish Date
12 Feb 2018

Abstract

Hate speech is a language that expresses a hatred of a group or individual who intends to insult or humiliate and the media can be found anywhere, one of them Twitter. Twitter is a social media that allows users to express feelings and opinions through tweets, including tweets that contain hate speech. Document or tweet data comes from previous research on hate speech. The method used in processing the document data is Backpropagation Neural Network with feature updates using Lexicon Based Features combined with Bag of Words. In this study using data as much as 500 data is divided into training data as much as 400 data and test data as much as 100 data. From the evaluation test results, when using Lexicon Based Features, the average value of f-measure is 0%, worse than using the Bag of Words with an average f-measure of 76.638%, while when Lexicon Based Features is combined with the Bag of Words got the best average score among the previous features with a f-measure of 78.081%. And the result Backpropagation Neural Network using Lexicon Based Features combined with Bag of Words is not better than Random Forest Decision Tree using n-gram from previous research.

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Journal Info

Abbrev

j-ptiik

Publisher

Subject

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Description

Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian ...