A Smart Public Service Optimization Model Using Linear Programming to Reduce the Number of Deaths

In everyday life, it is possible for people to need public services. What is meant by public services in this research are health, security, protection, and assistance services that threaten the safety of people's lives. Public services are needed by the community in every normal or emergency incident that must receive life-saving services as soon as possible, and every service that will be provided is not necessarily the same for all communities. This is because the incident, rescue needs, and location of the victim may vary, such as the occurrence of health problems, traffic accidents, crime incidents, and fires. This research uses the concept of “Smart Health and Safe City” which aims to optimize the smart public service model using linear programming to reduce the number of deaths by utilizing hospital agencies' limited resources to provide treatment as soon as possible, police agencies, fire agencies and Basarnas agencies, where when going to carry out public services, medical (m), police (p), fire brigade (f), and Basarnas (b) depart from the hospital location (ih), police location (ip), fire extinguisher location (if), and Basarnas location (ib) to location of victim (j) to provide public services in order for the modeling's output to address the issue of delivering intelligent services as early as possible which can reduce the number of deaths, minimize costs incurred, minimize service time and maximize resource utilization. possible, as well as obtaining the maximum value of the model's objective function. The simulation results, the maximum value of the objective function was obtained at 164,00000 at the 20th iteration step and produced a model that minimized the arrival time at the location of the service recipient.