<![CDATA[Islamic boarding schools are the oldest Islamic educational institutions in Indonesia that play an important role in shaping the character and moral development of the nation's generation. Along with the massive growth in the number of Islamic educational institutions, prospective students and parents often face the problem of information overload in determining the choice of institution that best suits their needs and applicable regulations. The selection process that has been carried out manually tends to be subjective and has not fully utilized a data-driven approach. This research aims to design and implement a recommendation system to assist prospective students in determining their choice of Islamic boarding school in a more objective, measurable, and efficient manner. The method used in the development of this system is a hybrid approach that combines content-based feature matching with collective user preference patterns through the integration of content-based filtering and collaborative filtering. The dataset used includes the profile data of Islamic boarding school institutions in the Kediri region as well as preference data from a number of respondents. The test results show that the integration of various similarity methods can produce accurate top-ranking recommendation lists. System performance evaluation using testing metrics shows an optimal level of data retrieval completeness, proving that the system is effective in presenting relevant and accountable recommendations for Islamic educational institutions in the digital era.]]>
