Pemodelan dan Simulasi Penyebaran Hoaks pada Media Sosial Menggunakan Model SIR

This research aims to analyze and simulate the dynamics of hoax dissemination on social media platforms using the Susceptible-Infected-Recovered (SIR) epidemiological model approach. The increasingly massive phenomenon of fake news spreading across digital platforms threatens social stability and public trust. Through the formulation of a system of non-linear differential equations, the user population is categorized into three main compartments: susceptible individuals, hoax spreader individuals, and recovered or verified individuals. This study examines the equilibrium points of the system and calculates the basic reproduction number to determine the stability threshold for misinformation spread. Numerical simulation results demonstrate that without intervention, fake news narratives spread aggressively and form an endemic pattern within the social network. However, the implementation of intervention scenarios consisting of enhanced digital literacy and increased information verification rates significantly reduces the basic reproduction number below unity. Consequently, the peak of the hoax transmission curve flattens, enabling the population to rapidly reach a hoax-free state. These findings offer theoretical contributions to applied mathematics while serving as practical reference for policymakers in mitigating digital misinformation.