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All Journal Journal of Computer Networks, Architecture and High Performance Computing Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Rahmansyah, Ferdian
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Computer Science & IT Education Electrical & Electronics Engineering

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Implementasi Lexicon Based dan Multinomial Naive Bayes pada Analisis Sentimen Produk Skincare di Website Sociolla Rahmansyah, Ferdian; Sriyanto, Sriyanto
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2025: SNESTIK V
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2025.7353

Abstract

Bumi menghadapi tantangan pemanasan global yang menyebabkan cuaca ekstrem, yang berdampak negatif pada kesehatan kulit seperti kerusakan, penuaan dini, dan risiko kanker kulit. Penggunaan produk perawatan kulit menjadi penting untuk melindungi dan mengatasi masalah kulit selama cuaca ekstrem. Platform e-commerce seperti Sociolla memudahkan pencarian dan pembelian produk skincare. Namun, konsumen perlu berhati-hati dalam memilih produk, mengingat kualitas dan reaksi kulit terhadap produk dapat berbeda-beda. Membaca ulasan produk dari pengguna lain dan menggunakan analisis sentimen dapat membantu konsumen membuat keputusan yang lebih cerdas. Analisis sentimen menggunakan metode lexicon based dan multinomial Naive Bayes untuk mengklasifikasikan ulasan menjadi positif, netral, atau negatif, memungkinkan konsumen menyaring ulasan dengan efisien dan efektif.
Sentiment Analysis of Skincare Products Using Lexicon and Multinomial Naive Bayes on The Sociolla Website Rahmansyah, Ferdian; Sriyanto, Sriyanto; Lestari, Sri; Irianto, Suhendro Yusuf
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.7048

Abstract

Global warming has triggered extreme weather that negatively affects skin health, including damage, premature aging, and increased risk of skin cancer, prompting the use of skincare products. E-commerce platforms like Sociolla simplify skincare purchases, but the abundance of choices and varying skin reactions make product selection challenging. This study aims to assist consumers in making smarter purchase decisions by analyzing user reviews using sentiment analysis with a lexicon-based approach and the Multinomial Naive Bayes algorithm to classify reviews as positive or negative. The process includes data collection, text preprocessing, model development, and performance evaluation. The results show that this method achieved an accuracy of 80,64%, demonstrating its effectiveness in helping consumers filter reviews and select appropriate skincare products.
Co-Authors Sri Lestari Sriyanto Sriyanto Y. Suhendro