SENTIMEN ANALYSIS TERHADAP NILAI KEPERCAYAAN SEBUAH ONLINE SHOP DI INSTAGRAM

Authors

  • Yan Puspitarani Universitas Widyatama

DOI:

https://doi.org/10.33197/jitter.vol2.iss1.2015.74

Keywords:

sentiment analysis, lexicon analysis, machine learning for sentiment

Abstract

[id]

Abstrak

Instagram menjadi tempat yang menarik untuk memasarkan produk. Dengan modal foto dan caption yang menarik, online shop akan mendapatkan followers yang kemungkinan besar tertarik untuk membeli produk mereka. Akan tetapi, seiring dengan mudahnya membuat akun Instagram, tingkat kepercayaan pembeli terhadap online shop tersebut menjadi hal yang paling penting. Oleh karena itu, diperlukan review terhadap online shop tersebut. Salah satu caranya adalah dengan memanfaatkan sentimen analysis terhadap komentar-komentar pada foto dan caption di akun Instagram online shop yang bersangkutan. Model sistem untuk proses review menggunakan sentiment analysis pun diusulkan pada paper ini. Proses sentiment akan menggabungkan pendekatan lexicon dan machine learning. Data yang akan digunakan adalah komentar-komentar terhadap foto dan caption beberapa online shop di Instagram.

Kata Kunci :

sentiment analysis, lexicon analysis, machine learning for sentiment

 

[en]

Abstract

Instagram became an attractive place to market the product. With attractive photos and captions, online shop will gain followers who are interested in buying their products. However, Instagram account can create easily so the level of buyer confidence to shop online has become the most important thing. Therefore, the review of the online shop is required. The review can be used by sentiment analysis to the comments of photos and captions in the online shop Instagram account. A model system for the review process using sentiment analysis was proposed in this paper. Sentiment process will combine lexicon and machine learning approaches. Data will be used in this study are comments on photos and captions several online shop on Instagram.

Keywords:

sentiment analysis, lexicon analysis, machine learning for sentiment

Downloads

Download data is not yet available.

Downloads

Published

2015-12-15

How to Cite

[1]
Y. Puspitarani, “SENTIMEN ANALYSIS TERHADAP NILAI KEPERCAYAAN SEBUAH ONLINE SHOP DI INSTAGRAM”, JITTER, vol. 2, no. 1, Dec. 2015.

Issue

Vol. 2 No. 1 (2015)

Section

Articles

License

Submission of a manuscript implies that the submitted work has not been published before (except as part of a thesis or report, or abstract); that it is not under consideration for publication elsewhere; that its publication has been approved by all co-authors. If and when the manuscript is accepted for publication, the author(s) still hold the copyright and retain publishing rights without restrictions. Authors or others are allowed to multiply the article as long as not for commercial purposes. For the new invention, authors are suggested to manage its patent before published. The license type is CC-BY-SA 4.0.

Most read articles by the same author(s)