Design of A Property Product Recommendation System Using Association Rule Method Based on User Interaction Patterns

Authors

  • Susi Wagiyati Purtiningrum Universitas Persada Indonesia Y.A.I, Indonesia
  • Yudi Irawan Chandra Sekolah Tinggi Manajemen Informatika dan Komputer Jakarta STI&K, Indonesia https://orcid.org/0000-0002-7850-8707
  • Dian Gustina Universitas Persada Indonesia Y.A.I, Indonesia
  • Nafisah Yuliani Universitas Persada Indonesia Y.A.I, Indonesia
  • Fahrul Nurzaman Universitas Persada Indonesia Y.A.I., Indonesia
  • Jhonny Z A Universitas Persada Indonesia Y.A.I, Indonesia
  • Agus Wismo Universitas Persada Indonesia Y.A.I, Indonesia

DOI:

https://doi.org/10.31098/icmrsi.v1i.787

Keywords:

Property Recommendation System, Association Rule Method, User Interaction Patterns, Personalized Suggestions, Real Estate Decision-making

Abstract

This work creates an association rule-based real estate product recommendation system. Personalizing property suggestions based on user behaviour optimises property searches. Data-driven insights enhance dynamic property market user experience. Association rules alter property advice. Data-driven insights and adaptability improve property search by proposing homes depending on user engagement patterns. Strong algorithms establish location, budget, and property associations, and association rule technology and user interaction patterns increase property recommendations. Personalized property discovery uses accurate and adaptive suggestions from continuous learning. Results reveal that user interaction pattern-based association rule techniques improve property suggestion accuracy and personalization. The system's tailored advice improves property market decisions, confirming its usefulness and adaptability. Insufficient user data might distort suggestions, especially for specific interests. Not enough user diversity can lower system accuracy. User data and privacy must be secured to optimize the recommendation system. Association rules and user engagement patterns can transform property recommendations. This innovative technique can improve property searches, provide personalized ideas, and help consumers make informed decisions in a competitive market.

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Published

2024-08-12

How to Cite

Purtiningrum, S. W. ., Chandra, Y. I., Gustina, D., Yuliani, N., Nurzaman, F., A, J. Z., & Wismo, A. (2024). Design of A Property Product Recommendation System Using Association Rule Method Based on User Interaction Patterns. Proceeding of the International Conference on Multidisciplinary Research for Sustainable Innovation, 1, 81–94. https://doi.org/10.31098/icmrsi.v1i.787