Analisis Perbandingan Kinerja Binary Search Tree dan AVL Tree dalam Sistem Pencarian Data Mahasiswa
Abstract
Information retrieval systems are a crucial part of data management, particularly in academic systems that store a large amount of student data. Search effectiveness is greatly influenced by the format and organization of the data. This study aims to evaluate and compare the performance of two types of tree data structures, namely Binary Search Trees and AVL Trees, in student data retrieval activities. Testing was conducted using numerical datasets reflecting student information with varying amounts of data: 20, 40, 60, 80, and 100. Parameters used in the assessment included tree height and data search duration. The algorithm was implemented using the Python programming language. The test results show that Binary Search Trees tend to have tree heights that increase significantly with increasing data volume due to the absence of a balancing mechanism. Meanwhile, AVL Trees can maintain the balance of their tree structure through a rotation process that makes the tree height more consistent. In addition, search time in AVL Trees also appears faster than Binary Search Trees, especially when the amount of data encountered is larger. Therefore, AVL Trees are considered more efficient and ideal for implementation in student data retrieval systems that require fast and stable searches.
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