Recommender System for Book Review based on Clustering Algorithms

• Published in: Journal of Applied Data Sciences
• Main Author: Udariansyah D.; Kurniawan T.B.; Dewi D.A.; Zakaria M.Z.; Hanan N.S.B.A.
• Format: Article
• Language: English
• Published: Bright Publisher 2025
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216783433&doi=10.47738%2fjads.v6i1.492&partnerID=40&md5=81f8f1ce0765d2ec3fb91064be288f82

Book reviews show the expression of the reviewers that are to be evaluated and describe the book. Today, the amount of the book is growing rapidly, and it offers people a lot of choices. The recommender system on book reviews is mostly mentioned, and we will recommend a book based on the keyword selected. This study highlights two primary objectives. The first objective is to identify the keywords of the book review, and the last objective is to design and develop a book review analysis visualization using the result of the k-means clustering algorithm. The methodology of this research consists of ten phases, which start with the preliminary study, knowledge acquisition and analysis phase, data collection phase, data pre-processing phase, and modeling phase. The research then continues with the design and implementation, dashboard development, testing and evaluation, and finally, the documentation phase. The data from this study is scraped from Amazon.com and focuses on three genres: Fiction and Fantasy, Mystery and Thriller, and Romance. All the data will be clean before it can be applied to k-means clustering. The result of clustering will define the keywords for every genre and will compare with the keywords for each book that was collected from Amazon.com. © 2025, Bright Publisher. All rights reserved.