Interactive Live Streaming Website with Cloud Computing and AI Assistant Integration - Tantra Adlillah, Satria; Rosita, Ai (Paradigma - Jurnal Komputer dan Informatika, 2026)
Live streaming platforms continue to face persistent challenges related to high latency, limited scalability, and insufficient real-time interactivity, which degrade user experience and hinder audience engagement. This study aims to address these limitations by developing StreamCats, a third-party interactive web-based live streaming system that integrates cloud computing infrastructure, WebSocket-based real-time communication, and an AI assistant. The system was developed using Object-Oriented Methodology (OOM) and the Rational Unified Process (RUP), implemented with Next.js, Socket.IO, Supabase, and Puter.js, while TikTok live event connectivity was achieved through WebSocket reverse engineering. System performance was evaluated through stress testing using Apache JMeter under 10, 50, and 100 concurrent user scenarios, functional validation of six core modules, and usability testing involving ten participants. The results demonstrate that under 100 concurrent users, the system maintained an average latency of 2,180.3 ms (well below the 5,000 ms threshold), a response time of 139 ms, CPU usage of 1.13%, and a throughput of 89.8 requests per second, outperforming comparable platforms Indofinity (57 req/s) and Tikfinity (19.5 req/s). All six modules passed functional tests, and 90% of participants successfully completed usability tasks with an average comprehension time of under five minutes. These findings confirm that the integration of cloud computing and AI-driven assistance significantly enhances scalability, responsiveness, and user experience in interactive live streaming environments, establishing StreamCats as a viable and competitive foundation for multi-platform real-time streaming solutions