| Summary: | Electronic Commerce (E-Commerce) is a type of commerce that takes place online. The most used platform based on frequently visited in Malaysia is Shopee. According to a questionnaire survey of 102 respondents, 95.1% agreed that manually comparing Shopee product information takes time. Manual analyzing a group of similar products is notoriously complicated, and finding informative reviews for product purchases is becoming increasingly challenging. This study aims to obtain Shopee information from the real-time Shopee website. Hence, Intelligence Shopee Product Comparison (i-SPC), aims to design a web-based application system that compares Shopee product information from different shops using the Naïve Bayes algorithm. The user can copy and paste the chosen Shopee product link to a maximum of ten links for comparison. The i-SPC displays the information based on seven focused factors and categorizes whether the pasted link is “recommended” or “not recommended”. The visualization result uses a bar chart to show four types of information: shop rating, product price, followers, and chat response. Testing phases have proven that the classifier accomplished all the research’s objectives and successfully classified Shopee product information with 87.50% accuracy, which is considered “good”. All test cases for the functionality test proved that the i-SPC successfully solved the problem. Therefore, it can be concluded that i-SPC overcame the problem and improved the product comparison process. © 2024, Semarak Ilmu Publishing. All rights reserved.
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