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All Journal International Journal of New Media Technology Jurnal ULTIMATICS Jurnal ULTIMA Computing Jurnal Bumigora Information Technology (BITe)
Fenina Adline Twince Tobing
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Journal : International Journal of New Media Technology

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Sentiment; Clustering; K-Means Analysis Sentiment in Bukalapak Comments with K-Means Clustering Method Rena Nainggolan; Fenina Adline Twince Tobing; Eva J.G Harianja
IJNMT (International Journal of New Media Technology) Vol 9 No 2 (2022): IJNMT : International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v9i2.2914

Abstract

Technological development are very fast ini this era of globalization, to facilitate the work of many aspevt that can be utilized, as well as for the flow of information. By applying computer technology in varios fields, such as educations, entertainment, healt, tourism, culinary and so on. Clustering id one of the Data Mining techniques. Clustering works by combining a number of data or objects into one cluster, with the aim that each data ini one cluster will have data that is a similar as possible and different from data or objects in other groups. K-Means Clustering has the ability to perform computations that are relatively fast and efficient in combining large amounts of data. In this research, there are 1407 comments which will training data and testing data.
Co-Authors Eva Julia Gunawati Harianja James Ronald Tambunan M Iqbal Dzulhaq Pomalingo, Suwito Prayogo . Ramzi Fajar Sidiq Rena Nainggolan