Indonesian Journal of Statistics and Its Applications
Vol 4 No 1 (2020)

COMPARISON OF K-MEANS CLUSTERING METHOD AND K-MEDOIDS ON TWITTER DATA

Cahyani Oktarina (Department of Statistics, IPB University, Indonesia)
Khairil Anwar Notodiputro (Department of Statistics, IPB University, Indonesia)
Indahwati Indahwati (Department of Statistics, IPB University, Indonesia)



Article Info

Publish Date
28 Feb 2020

Abstract

The presidential election is one of the political events that occur in Indonesia once in five years. Public satisfaction and dissatisfaction with political issues have led to an increase in the number of political opinion tweets. The purpose of this study is to examine the performance of the k-means and k-medoids method in the Twitter data and to tweet about the presidential election in 2019. The data used in this study are primary data taken from Muhyi's research, then mining the text against data obtained. Because this data has been processed by Muhyi to analyze the electability of the 2019 presidential candidate pairs, for this journal needs a preprocessing was carried out to analyze the tendency of tweets to side with the candidate pairs of one or two. The difference in the pre-processing of this research with previous research is that there is a cleaning of duplicate data and normalizing. The results of this study indicate that the optimal number of clusters resulting from the k-means method and the k-medoid method are different.

Copyrights © 2020






Journal Info

Abbrev

ijsa

Publisher

Subject

Computer Science & IT Mathematics Other

Description

Indonesian Journal of Statistics and Its Applications (eISSN:2599-0802) (formerly named Forum Statistika dan Komputasi), established since 2017, publishes scientific papers in the area of statistical science and the applications. The published papers should be research papers with, but not limited ...