ANALISIS DAN OPTIMASI PADA DATABASE RELASIONAL MENGGUNAKAN INDEKS DAN NORMALISASI TINGKAT LANJUT: STUDI KASUS SISTEM INFORMASI AKADEMIK

Abstract

Implementing advanced normalization in relational databases is a fundamental standard to ensure data integrity in Academic Information Systems (SIAKAD). However, normalized data structures often lead to increased query complexity and latency as the volume of student grade data expands. This study aims to analyze and optimize query performance in relational databases by applying the B-Tree Indexing technique. The research methodology employs a quantitative experimental approach, simulating workload on a dataset containing 10,000 grade history records. Testing focuses on comparing execution time before and after optimization. Results indicate that under standard table conditions without indexing, the data retrieval mechanism using a full table scan requires an average time of 0.0029 seconds. Following the application of indexing on key attributes, execution time decreased significantly to 0.0004 seconds. This represents an 84.5% increase in performance efficiency and a shift in the data access method to an index range scan. It is concluded that the combination of valid normalization design and appropriate indexing strategies is a crucial solution for handling high academic data access loads.