PREDICTION OF THE GROWTH AND SPREAD OF LIVE STREAMING AS A MARKETING MEDIA

• Main Author: Kurniawan, Michelle
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/81828
• Institution: Institut Teknologi Bandung

Live streaming is the real-time transmission of information over the internet in video format. Live streaming can be used for various purposes, one of which is as a marketing media, known as live marketing. The phenomenon of live marketing has proliferated since the outbreak of the Covid-19 pandemic in 2020. The development of live marketing has not been separated from the influence of influencers. Influencers are individuals who promote products or brands. In this final project, it is assumed that the growth of interest in live streaming follows logistic growth, the Richards curve, and the Gompertz curve. Subsequently, parameter estimation of the growth rate of followers from TikTok, Shopee, and Instagram is performed. From the results of the analysis and numerical simulations, the growth model that can represent the data based on the characteristics of the S-curve is the Richards curve. To examine the impact of live streaming growth on community groups, two models will be constructed to observe the dynamics of spread without and with influencers. The model used is adapted and modified from the SIR (Susceptible, Infected, Recovered) compartmental model. For the model without influencers (MFB), the population is divided into three classes: interest, followers, and boredom. Meanwhile, for the model with influencers (MFB-CI), there are additional populations: potential influencers and influencers. Based on the results of analysis and numerical simulations, an increase in the growth rate in the MFB model leads to an increase in the number of followers and a shorter time required to reach the peak trend. The interaction rate in the MFB-CI model is inversely proportional to the population of interest and directly proportional to the population of follower. Furthermore, using the basic reproduction number ????0, it was found that the growth rate of followers and the rate of interest increase (????) in the MFB model, as well as the rate of interest interaction with influencers and the rate of follower interaction with potential influencers in the MFB-CI model, contribute to the increase in ????0