EMITTER International Journal of Engineering Technology
Vol 8 No 1 (2020)

Unsupervised Twitter Sentiment Analysis on The Revision of Indonesian Code Law and the Anti-Corruption Law using Combination Method of Lexicon Based and Agglomerative Hierarchical Clustering

Nur Restu Prayoga (Faculty of Computer Science, Universitas Narotama, Indonesia)
Tresna Maulana Fahrudin (Faculty of Computer Science, Universitas Narotama, Indonesia)
Made Kamisutara (Faculty of Computer Science, Universitas Narotama, Indonesia)
Angga Rahagiyanto (Department of Medical Records, Politeknik Negeri Jember, Indonesia)
Tahegga Primananda Alfath (Faculty of Law, Universitas Narotama, Indonesia)
Latipah (Faculty of Computer Science, Universitas Narotama)
Slamet Winardi (Faculty of Computer Science, Universitas Narotama, Indonesia)
Kunto Eko Susilo (Faculty of Computer Science, Universitas Narotama, Indonesia)



Article Info

Publish Date
02 Jun 2020

Abstract

The rejection on ratification of the revision of Indonesian Code Law or known as RKUHP and Corruption Law raises several opinions from various perspectives in social media. Twitter as one of many platforms affected, has more than 19.5 million users in Indonesia. Twitter is one of many social media in Indonesia where people can share their views, arguments, information, and opinions from all points of view. Since Twitter has a great diversity of users, it needs a system which is designed to determine the opinion tendency towards the problems or objects. The purpose of this study is to analyze the sentiment of Twitter users' tweets to reject the revision of the Law whether they have positive or negative sentiments using the Agglomerative Hierarchical Clustering method. The data that being used in this study were obtained from the results of crawling tweets based on hashtag (#) (#ReformasiDikorupsi). The next stage is pre-processing which consists of case folding, tokenizing, cleansing, sanitizing, and stemming. The extraction features Lexicon Based and Term Frequency (TF) which performs the process automatically. In the clustering stage, two clusters use three approaches; single linkage, complete linkage and average linkage. In the accuracy calculation phase, the writer uses the error ratio, confusion matrix, and silhouette coefficient. Therefore, the results are quite good. From 2408 tweets, the highest accuracy results are 61.6%.

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Journal Info

Abbrev

EMITTER

Publisher

Subject

Computer Science & IT

Description

EMITTER International Journal of Engineering Technology is a BI-ANNUAL journal published by Politeknik Elektronika Negeri Surabaya (PENS). It aims to encourage initiatives, to share new ideas, and to publish high-quality articles in the field of engineering technology and available to everybody at ...