Peningkatan Performa Restful Api Menggunakan Teknik Caching Dan Query Optimization

RESTful APIs play a pivotal role in data exchange within modern application architectures. However, the traffic monitoring system at Bengkalis State Polytechnic faces performance issues due to periodic polling techniques, resulting in high traffic loads, latency, and response failures. This research aims to analyze the effectiveness of Redis-based caching and query optimization (including indexing and query simplification) in improving API performance. The research method employs an experimental approach with load testing using Apache JMeter under load scenarios ranging from 50 to 250 virtual users. The results demonstrate significant performance improvements post-optimization. In the normal load scenario (50 users), the average response time was successfully reduced from 36,307 ms to 192 ms. Throughput increased drastically from 1.1 to 11.89 requests per second. Furthermore, the optimization successfully reduced the error rate from the 18-29% range in the baseline condition to 0% at medium loads, while maintaining system stability at peak loads. This study concludes that the combination of caching and query optimization is highly effective in handling high traffic loads in polling-based systems.