Sentiment Analysis on Natural Skincare Products
Skincare Industry was increasing rapidly year by year. In contrast, many skincare companies have brought their products and originality to attract many customers. However, due to many controversial cases involving the chemical substance in skincare products, the company switched to something more na...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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INTI International University
2022
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/1667/ http://eprints.intimal.edu.my/1667/1/jods2022_12.pdf |
| _version_ | 1848766801068949504 |
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| author | Fadly, . Dewi Marlina, . Tri Basuki, Kurniawan Mohd Zaki, Zakaria Siti Farahnasihah, Abdullah |
| author_facet | Fadly, . Dewi Marlina, . Tri Basuki, Kurniawan Mohd Zaki, Zakaria Siti Farahnasihah, Abdullah |
| author_sort | Fadly, . |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | Skincare Industry was increasing rapidly year by year. In contrast, many skincare companies have brought their products and originality to attract many customers. However, due to many controversial cases involving the chemical substance in skincare products, the company switched to something more natural: natural skincare. With much natural skincare in the shop, many customers face the problem of which one to buy. This research helps customers by giving a guideline for the customers to make the decision. Sentiment Analysis is used to analyze the reviews from past customers and create a visualization containing positivity and negativity of all the reviews. Five classifiers were used to produce the best result: Naïve Bayes, KNN, SVM, Decision Tree, and Deep Learning. The reviews were collected from Sephora.com websites, and the tools used in analyzing the reviews are Python and RapidMiner. Reviews collected are 10000 data from a website. The result shows that Deep Learning and Decision Tree are classifiers in sentiment analysis with almost 80% accuracy and 60% F1 measurement. F1 measure is a measure of a test's accuracy. For future enhancements, the data collected can be more than this research, and no data imbalance was created. |
| first_indexed | 2025-11-14T11:56:55Z |
| format | Article |
| id | intimal-1667 |
| institution | INTI International University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:56:55Z |
| publishDate | 2022 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-16672024-05-07T09:47:52Z http://eprints.intimal.edu.my/1667/ Sentiment Analysis on Natural Skincare Products Fadly, . Dewi Marlina, . Tri Basuki, Kurniawan Mohd Zaki, Zakaria Siti Farahnasihah, Abdullah HF Commerce QA75 Electronic computers. Computer science QA76 Computer software Skincare Industry was increasing rapidly year by year. In contrast, many skincare companies have brought their products and originality to attract many customers. However, due to many controversial cases involving the chemical substance in skincare products, the company switched to something more natural: natural skincare. With much natural skincare in the shop, many customers face the problem of which one to buy. This research helps customers by giving a guideline for the customers to make the decision. Sentiment Analysis is used to analyze the reviews from past customers and create a visualization containing positivity and negativity of all the reviews. Five classifiers were used to produce the best result: Naïve Bayes, KNN, SVM, Decision Tree, and Deep Learning. The reviews were collected from Sephora.com websites, and the tools used in analyzing the reviews are Python and RapidMiner. Reviews collected are 10000 data from a website. The result shows that Deep Learning and Decision Tree are classifiers in sentiment analysis with almost 80% accuracy and 60% F1 measurement. F1 measure is a measure of a test's accuracy. For future enhancements, the data collected can be more than this research, and no data imbalance was created. INTI International University 2022-09 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1667/1/jods2022_12.pdf Fadly, . and Dewi Marlina, . and Tri Basuki, Kurniawan and Mohd Zaki, Zakaria and Siti Farahnasihah, Abdullah (2022) Sentiment Analysis on Natural Skincare Products. Journal of Data Science, 2022 (12). pp. 1-17. ISSN 2805-5160 http://ipublishing.intimal.edu.my/jods.html |
| spellingShingle | HF Commerce QA75 Electronic computers. Computer science QA76 Computer software Fadly, . Dewi Marlina, . Tri Basuki, Kurniawan Mohd Zaki, Zakaria Siti Farahnasihah, Abdullah Sentiment Analysis on Natural Skincare Products |
| title | Sentiment Analysis on Natural Skincare Products |
| title_full | Sentiment Analysis on Natural Skincare Products |
| title_fullStr | Sentiment Analysis on Natural Skincare Products |
| title_full_unstemmed | Sentiment Analysis on Natural Skincare Products |
| title_short | Sentiment Analysis on Natural Skincare Products |
| title_sort | sentiment analysis on natural skincare products |
| topic | HF Commerce QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://eprints.intimal.edu.my/1667/ http://eprints.intimal.edu.my/1667/ http://eprints.intimal.edu.my/1667/1/jods2022_12.pdf |