Analisis Sentimen Online Review Pengguna Bukalapak Menggunakan Metode Algoritma TF-IDF

  • Pradita Eko Prasetyo Utomo Universitas Jambi
  • Manaar Universitas Jambi
  • Ulfa Khaira Universitas Jambi
  • Tri Suratno Universitas Jambi
Keywords: Sentiment Analysis, TF-IDF Algorithm, preprocessing, e-commerce, customers

Abstract

Bukalapak is one of the Customer-To Customer (C2C) e-commerce models. This model is the most widely applied and found on e-commerce sites in Indonesia. The Customer-To Customer (C2C) market is currently still dominant in Indonesia's online retail market. Data collected from Euromonitor estimates that the C2C market contributed 3% of the retail market in Indonesia in 2017, while the B2C market contributed 1.7%. One text mining analysis is that sentiment analysis can be applied to companies that issue a product or service and provide services to receive opinions (feedback) from consumers for the product. Sentiment analysis is applied to classify positive, negative, and neutral feedback from consumers so as to speed up and simplify the company's task to review their product deficiencies. The researcher conducted further analysis on Bukalapak user reviews to find out how user comments or opinions were on Bukalapak using the TF-IDF Algorithm method. And it can be concluded that based on customer review reviews in Bukalapak have a good rating or perception of this Vans shoe product. Can be seen from the results of Sentiments, Sentiment Visualization and WordCloud Visualization which shows that positive reviews have a higher frequency of 70%.

 

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Published
2019-12-31
How to Cite
Utomo, P. E. P., Manaar, Khaira, U., & Suratno, T. (2019). Analisis Sentimen Online Review Pengguna Bukalapak Menggunakan Metode Algoritma TF-IDF. JUSS (Jurnal Sains Dan Sistem Informasi), 2(2), 35-39. Retrieved from https://online-journal.unja.ac.id/JUSS/article/view/8469