Honors Thesis Archive

AuthorCatie Oerther
TitleAnalyzing the Need for Nonprofits in the Housing Sector: A Predictive Model Based on Location
DepartmentComputer Science
AdvisorTyler Highlander
Year2023
HonorsUniversity Honors
Full TextView Thesis (524 KB)
AbstractThis paper aims to present a study on developing a program that assists nonprofit organizations in determining the ideal location for building their facilities based on community needs, thus maximizing their potential for success. The study highlights the importance of location in the success of nonprofit organizations, and the challenges they face in identifying suitable areas for their operations. The paper reviews existing literature on nonprofit organizations, location analysis, and data analysis techniques, and proposes a methodology for developing the program. The methodology involves data collection and analysis, and machine learning algorithms to predict community needs. The program provides a user-friendly interface for nonprofit organizations to access and analyze the data and offers recommendations for suitable locations based on their criteria. The study concludes that the proposed program can be a valuable tool for nonprofit organizations to make informed decisions about their location and maximize their potential for success in serving their communities.

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