Analysis Of Item-Based Collaborative Filtering For Sales Of Processed Oil Palm Products
Abstract
Abstract- The sales system for processed palm oil necessitates a recommendation system that offers product suggestions to users, facilitating their selection of sales items for processed palm oil products. This study used the Item-Based Collaborative Filtering approach, which identifies the similarity between items. The system will assess the rating of each item and compute the similarity value utilising the Pearson correlation-based similarity formula. Companies will exhibit greater interest in product sales that possess identical similarity values. This article presents recommendations for system development concerning processed products intended for the sale of technology-based items that employ item-based collaborative filtering methods. It specifies a recommended selling value for processed palm oil products, with a Mean Absolute Error (MAE) of 10.463126965591, derived from the equation 5/1, yielding a final result of -5. The execution of the sales suggestions for processed palm oil products indicates that the items with the highest similarity value calculations are i4 and i5. PT. Sugih Riesta Jaya employs the Item-Based collaborative filtering method to enhance sales of refined palm oil products, thereby facilitating sales assistance and providing the public with sales information and recommendations for essential refined palm oil products..
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