Analisis Sentimen Ulasan E-Commerce Pakaian Berdasarkan Kategori dengan Algoritma Convolutional Neural Network

  • I Made Adi Susilayasa Universitas Udayana
  • Anak Agung Istri Eka Karyawati
  • Luh Gede Astuti
  • Luh Arida Ayu Rahning Putri
  • I Gede Arta Wibawa
  • I Komang Ari Mogi

Abstract

Almost everyone looks at reviews before deciding to buy an item in e-commerce. Consumers say that online reviews influence their purchasing decisions. Based on these data, consumers need sentiment reviews to make a decision to choose a product/service. However, the results of the sentiment analysis are still less specific, so the review classification process is carried out based on the review category. Sentiment classification process based on clothing category is carried out using the Convolutional neural network method. The amount of data used is 3384 data with 3 categories. The category classification model shows good performance. When evaluated with testing data (unseen data), the accuracy value is 88%, the precision value is 88%, recall is 88% and the f1-score is 88%. For the sentiment classification model with the bottoms category, the resulting accuracy value is 80%, precision is 81%, recall is 80%, and f1-score is 79%. For the sentiment classification model with the dresses category, the accuracy value is 81%, precision is 81%, recall is 81%, and f1-score is 81%. For sentiment classification with the tops category the resulting accuracy value is 77%, precision is 77%, recall is 77%, and f1-score is 77%.

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Published
2022-07-08
How to Cite
SUSILAYASA, I Made Adi et al. Analisis Sentimen Ulasan E-Commerce Pakaian Berdasarkan Kategori dengan Algoritma Convolutional Neural Network. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 1, p. 1-12, july 2022. ISSN 2654-5101. Available at: <https://ojs.unud.ac.id/index.php/jlk/article/view/86503>. Date accessed: 08 dec. 2024. doi: https://doi.org/10.24843/JLK.2022.v11.i01.p01.

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