<![CDATA[The property industry has experienced rapid growth along with the increasing demand for housing and investment, driven by urbanization and changes in lifestyle. However, the provision of property information to prospective buyers still faces several challenges, particularly in terms of recommendation personalization, service response speed, and accuracy in matching customer needs with available property products. PT Spinindo Mitradaya, as one of the property developers, seeks to improve the quality of information services through the utilization of intelligent information technology systems. This study aims to develop a property recommendation system capable of providing automatic housing suggestions based on the initial preferences of prospective buyers. The system is developed using a knowledge-based system approach by applying the rule-based reasoning method and the forward chaining inference mechanism. User preference data are collected through a digital form containing information related to budget, preferred location, property type, and financing scheme. The data are then processed using logical rules in the form of if–then rules designed based on the characteristics of the projects and property types offered by the company. The implementation results show that the system is able to generate property recommendations, credit tenors, and installment estimations that match the needs of prospective buyers more quickly and accurately. The implementation of this system helps improve the efficiency of property information delivery and supports the initial decision-making process for the marketing team.]]>
