<![CDATA[The development of the education industry and other supporting sectors scattered in the Sleman Regency - Indonesia has influenced the mushrooming of boarding houses. It is essential to use business intelligence for boarding house investors to analyze market trends to produce a boarding property business that is not inferior to its competitors. This study aims to contribute to the boarding house investors to obtain information on the characteristics, relationships, and effects of boarding house facilities on the rental prices set to remain competitive in the market. A total of 658 boarding house data from an e-commerce platform was extracted using business intelligence web scraping to determine the characteristics of the boarding house market trend in Sleman Regency. Multinomial Logistic Regression was used to find out the facilities for rooms, bathrooms, shared services and equipment, and common rooms, making the difference in rental prices for superior, exclusive, intermediate, and standard boarding house classes. The Multinomial Logistic Regression analysis results revealed that boarding houses with high rental prices were more concerned with things directly felt by tenants (everything about their room needs). Meanwhile, boarding houses with affordable rental prices prioritized things that general tenants could use/utilized.]]>
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