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Nurul Dyah Mentari
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Analisis Sentimen Kurikulum 2013 Pada Sosial Media Twitter Menggunakan Metode K-Nearest Neighbor dan Feature Selection Query Expansion Ranking Nurul Dyah Mentari; Mochammad Ali Fauzi; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kurikulum 2013 has become a hot topic that is often discussed by society on Twitter. Twitter is one of the social media that used by a society to talk about a particular subject. This study attempted to analyze tweets about the Kurikulum 2013 by classifying whether it is a positive opinion or a negative opinion. Classification process is done by K-Nearest Neighbor method by using Query Expansion Ranking method for feature selection. There are 4 main processes in this analysis sentiment system that first is text pre-processing, term weighting (TF-IDF), feature selection, and classification. Based on the tests in this study proven that feature selection improve accuracy of systemresults. The best acuracy results of 96.36%was obtained when k = 1 and using a feature selection of 50% ratio. The test results by using selection feature of 50% ratio get higher accuracy than a system does not use the selection feature because some noise features that have been removed.
Co-Authors Lailil Muflikhah M. Ali Fauzi