A Web-Based Laptop Purchase Recommendation Model Using Natural Language Processing (NLP) on Marketplace Reviews

This system will use the Natural Language Processing (NLP) method to analyze user reviews. In addition, the Naive Bayes classification algorithm will be used to provide recommendations based on the analysis. The methods used include collecting laptop user review data from the Shopee platform, Natural Language Processing (NLP) for text analysis, classification with the Naive Bayes algorithm, developing a recommendation system, and evaluating the system using relevant metrics. The results of the study show that this model achieves an accuracy of 0.86 with a precision of 0.93 for positive reviews and 0.69 for negative reviews. Of the total 42 reviews tested, the system provides a recall of 0.87 for positive reviews and 0.82 for negative reviews. The total reviews in the dataset consist of 96 positive reviews and 43 negative reviews. This study is expected to contribute to the development of review-based recommendation systems, so that users can make the right decisions.

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Publication Details

Journal
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Published
2024-11-29
DOI
https://doi.org/10.30811/jaise.v4i2.6133
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
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article

A Web-Based Laptop Purchase Recommendation Model Using Natural Language Processing (NLP) on Marketplace Reviews

M Khadafi, Rahmad Hidayat, Irham Syahdana
Journal of Artificial Intelligence and Software Engineering (J-AISE)
Impact of AI and Big Data on Business and Society
article

A Web-Based Laptop Purchase Recommendation Model Using Natural Language Processing (NLP) on Marketplace Reviews

M Khadafi, Rahmad Hidayat, Irham Syahdana
article en

Abstract

This system will use the Natural Language Processing (NLP) method to analyze user reviews. In addition, the Naive Bayes classification algorithm will be used to provide recommendations based on the analysis. The methods used include collecting laptop user review data from the Shopee platform, Natural Language Processing (NLP) for text analysis, classification with the Naive Bayes algorithm, developing a recommendation system, and evaluating the system using relevant metrics. The results of the study show that this model achieves an accuracy of 0.86 with a precision of 0.93 for positive reviews and 0.69 for negative reviews. Of the total 42 reviews tested, the system provides a recall of 0.87 for positive reviews and 0.82 for negative reviews. The total reviews in the dataset consist of 96 positive reviews and 43 negative reviews. This study is expected to contribute to the development of review-based recommendation systems, so that users can make the right decisions.

Journal of Artificial Intelligence and Software Engineering (J-AISE)Vol. 4(2)
Peace, Justice and strong institutions
Openalex Percentile: Top 74%
Impact of AI and Big Data on Business and Society
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