Network prediction based on clustering: case study for human settlements along urban roads

Abstract

Indonesia is in a category with a very dense population of 279,918,617 people in July 2024. Population density can lead to a decrease in the quality of health services. One of the causes is the high rate of transmission of viral diseases in densely populated areas. For this reason, an innovative strategy is needed to inhibit the spread of the virus. Network clustering and predictive distribution techniques in delivering health logistics in densely populated areas can improve the efficiency and effectiveness of health logistics delivery. The techniques in delivering health logistics in densely populated areas can improve efficiency and effectiveness in dealing with the rate of virus spread. Based on these methods, the problem of delivering health logistics will be easy because zone predictions from network clustering results provide information on the location and density of the area. The method allows medical officers to prioritize the delivery zone for health logistics. This method can also overcome the next wave of viruses, such as COVID-19 and other infectious diseases.