This article presents a performance comparison between tree data structures and linked list data structures for managing human resources data with hierarchical relationships, including employee information such as ID, full name, position, department, and event records. The study aims to compare the speed of insertion, deletion, and searching for each structure, tested with datasets of 100, 1,000, and 10,000 records, each tested three times. The results show that the tree structure outperforms the linked list in data insertion, particularly with the 10,000-record dataset, achieving an insertion rate of 3.785 records per second and an average time of 264.28 milliseconds. In contrast, the linked list achieves only 0.107 records per second and an average time of 9,345.85 milliseconds. For searching and deleting data, both structures perform similarly. In conclusion, the tree structure is better suited for systems handling hierarchical data, as it can insert data quickly and handle larger datasets more efficiently, while the linked list may be more suitable for tasks with smaller datasets or without complex hierarchical relationships.