DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS

Yudi Irawan Chandra (), Susi Wagiyati Purtiningrum, Dian Gustina, Nafisah Yuliani, Fahrul Nurzaman, Jhonny Z.a and Agus Wismo
Additional contact information
Yudi Irawan Chandra: Sekolah Tinggi Manajemen Informatika dan Komputer Jakarta STI&K, Jakarta, Indonesia
Susi Wagiyati Purtiningrum: Universitas Persada Indonesia YAI, Jakarta, Indonesia
Dian Gustina: Universitas Persada Indonesia YAI, Jakarta, Indonesia
Nafisah Yuliani: Universitas Persada Indonesia YAI, Jakarta, Indonesia
Fahrul Nurzaman: Universitas Persada Indonesia YAI, Jakarta, Indonesia
Jhonny Z.a: Universitas Persada Indonesia YAI, Jakarta, Indonesia
Agus Wismo: Universitas Persada Indonesia YAI, Jakarta, Indonesia

Acta Informatica Malaysia (AIM), 2024, vol. 8, issue 2, 69-78

Abstract: This work creates an association rule-based real estate product recommendation system. Personalizing property suggestions based on user behavior 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 rule 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.

Keywords: Property recommendation system; ASSOCIATION rule method; User interaction patterns; Personalized suggestions; Real estate decision-making (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-69-78.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnaim:v:8:y:2024:i:2:p:69-78

DOI: 10.26480/aim.02.2024.69.78

Access Statistics for this article

Acta Informatica Malaysia (AIM) is currently edited by Associate Professor Dr. Shahreen Kasim

More articles in Acta Informatica Malaysia (AIM) from Zibeline International Publishing
Bibliographic data for series maintained by Zibeline International Publishing ( this e-mail address is bad, please contact ).