Application Of K-Nearest Neighbor Algoritma for Customer Review Sentiment Analysis at Ngeboel Vapestore Shop
This study applies the K-Nearest Neighbor (K-NN) algorithm to classify customer sentiments from online reviews about Ngeboel Vapestore, a local MSME in the vape industry. A total of 175 reviews from Google Review and Instagram were processed using standard NLP techniques and TF-IDF for feature extr...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
LPPM STIKI Malang
2025-06-01
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| Series: | J-Intech (Journal of Information and Technology) |
| Subjects: | |
| Online Access: | https://jurnal.stiki.ac.id/J-INTECH/article/view/1893 |
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| Summary: | This study applies the K-Nearest Neighbor (K-NN) algorithm to classify customer sentiments from online reviews about Ngeboel Vapestore, a local MSME in the vape industry. A total of 175 reviews from Google Review and Instagram were processed using standard NLP techniques and TF-IDF for feature extraction. The best K-NN model (k=3) achieved 85.4% accuracy. Although Logistic Regression achieved higher accuracy (92.6%), it failed to detect negative sentiment. The findings highlight the potential and limitations of K-NN for sentiment analysis in underexplored MSME contexts like vape retail. The study recommends further model improvements and broader MSME applications.
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| ISSN: | 2303-1425 2580-720X |