SKYLINE QUERY BASED ON USER PREFERENCES IN CELLULAR ENVIRONMENTS

The recommendation system is an important tool for providing personalized suggestions to users about products or services. However, previous research on individual systems using skyline queries has not considered the dynamic personal preferences of users. Therefore, this study aims develop model based current and user location in a mobile environment. We propose RFM (Recency, Frequency, Monetary) score-based algorithm predict This utilizes query method recommend local cuisine that aligns with attributes used selecting suitable include preferences, price, distance between seller. proposed been implemented JALITA mobile-based Indonesian system. results effectively matches Based implementation results, recommendations are provided anytime anywhere they located. In study, three objects generated: soto betawi (C5), Mie Aceh Daging Goreng (C4), Gado-gado (C3), which recommended (U1) (L1). exemplified one located at (U1L1), (C5) preference score 0.96, (C4) 0.93, (C3) 0.98. Thus, contributes field by considering preferences.