Abstract
In Indonesia, e-commerce platforms are rapidly growing as the number of visitors continues to increase. There is a product that is most often used, called Fast-Moving Consumer Goods. The customer's side wants affordable prices, so it is challenging for the product procurement team to prepare their own estimated prices and compare them quickly. In this study, a decision support system was designed by automating the product grouping process. The experiment used FMCGs textual data from various e-commerce sites and cluster data preparation with the help of Latent Semantic Analysis to reduce the TF-IDF weighting data dimension. The results showed that the effect of data preparation yielded a result of 0.092 outperforming data without stoplist and word-based stoplists available by the stopwords library, even though the execution time was 0.01 seconds longer than others.
Original language | English |
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Pages (from-to) | 455-462 |
Number of pages | 8 |
Journal | Procedia Computer Science |
Volume | 234 |
DOIs | |
Publication status | Published - 2024 |
Event | 7th Information Systems International Conference, ISICO 2023 - Washington, United States Duration: 26 Jul 2023 → 28 Jul 2023 |
Keywords
- Clustering
- Owner Estimate
- Procurement Team
- Textual Data