<![CDATA[The rapid advancement of information technology has significantly increased the volume and complexity of data managed by organizations across various sectors. This condition requires Database Management Systems (DBMS) to process data efficiently while maintaining accuracy, security, and reliability. One of the key factors influencing DBMS performance is the implementation of programming algorithms for searching, sorting, indexing, query optimization, transaction management, and data storage. This article aims to analyze the role of programming algorithms in improving data processing efficiency through DBMS optimization. The study employs a literature review approach by examining relevant books and scientific publications. The findings indicate that implementing algorithms such as Binary Search, Merge Sort, Quick Sort, B-Tree, B+Tree, Hashing, Indexing, Caching, Query Optimization, and Transaction Processing improves query execution speed, optimizes computational resource utilization, maintains data consistency, and enhances system security. Although challenges remain, including Big Data, real-time processing, and scalability, appropriate algorithm implementation significantly improves DBMS efficiency, performance, speed, accuracy, and reliability, enabling effective data management across various application domains.]]>
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