By leveraging Data Mining technology, specifically the Decision Tree algorithm, this study focuses on clustering data based on age and gender to enhance the efficiency and personalization of services in nursing homes. The data used spans from January 2024 to April 2024, encompassing 333 rows that have been processed for classification purposes. The developed Decision Tree model accurately separates the data based on age, with results showing the gender distribution within each age group. These findings indicate that the Decision Tree algorithm is effective in identifying gender based on specific age boundaries, which can be applied to improve the quality and effectiveness of nursing home services. The analysis provides valuable insights for better planning and management of social services, making this approach relevant for demographic data management in nursing homes.
Copyrights © 2024