Indonesian Journal of Applied Statistics
Vol 2, No 1 (2019)

Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier

Lingga Aji Andika (Universitas Sebelas Maret)
Pratiwi Amalia Nur Azizah (Universitas Sebelas Maret)
Respatiwulan Respatiwulan (Universitas Sebelas Maret)

Article Info

Publish Date
05 Jul 2019

Abstract

Indonesia is one of the countries that adheres to a democratic system. In the course of a democratic system it is marked by periodic general elections. In 2019 Indonesia held a general election simultaneously to elect the President, DPR, DPRD and DPD. After the election, a lot of opinion arise within the community, including on social media twitter. One of the topics discussed was the results of the quick count of the presidential election. Therefore, a method that can be used to analyze sentiment from the quick count opinion is needed, that is naive Bayes method. The aims of this study are to find the best naive Bayes model and to classify sentiments. The result shows the best accuracy of 82.90% with α = 0.05. The classification obtained is 34.5% (471) positive tweets and 65.5% (895) negative tweets on the results of the quick count.Keywords : sentiment analysis, naive Bayes classifier, elections, quick count

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Journal Info
Indonesian Journal of Applied Statistics
Website

Abbrev

ijas

Publisher

Universitas Sebelas Maret

Subject

Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science

Description

Indonesian Journal of Applied Statistics (IJAS) is a journal published by Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. This journal is published twice every year, in May and November. The editors receive scientific papers on the results of research, scientific ...