Cafe Selection Recommendation System in Semarang City Uses Collaborative Filtering Method with Item Based Filtering Algorithm


Sistem Rekomendasi Kafe di Kota Semarang Menggunakan Collaborative Filtering Dengan Algoritma Item Based Filtering


  • (1) * Alldie Refkrisnatta            Stikubank University Semarang  
            Indonesia

  • (2)  Dewi Handayani            Stikubank University Semarang  
            Indonesia

    (*) Corresponding Author

Abstract

The cafe selection recommendation system in the city of Semarang aims to provide recommendations for users in finding the desired café according to the type of café expected. This recommendation system serves to predict an item that is of interest to the user. Implementation of recommendation system using Collaborative Filtering and Item Based Filtering algorithms. Collaborative filtering is a recommendation system algorithm where recommendations are given based on consideration of data from other users while the Item Based Filtering algorithm to provide recommendations based on similarities between customer tastes and café characteristics.

Author Biographies

Alldie Refkrisnatta, Stikubank University Semarang

Informatics Engineering Study Program

Dewi Handayani, Stikubank University Semarang

Informatics Engineering Study Program

References

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Published
2022-10-19
 
Section
Computer Engineering