CROWD IDENTIFICATION ON RSSI-WIFI BASED INDOOR POSITION TRACKING SYSTEM - Ezra Yahya, Jovan
Corona Virus Disease 2019 (COVID-19) is a disease that spreads very rapidly, especially in Indonesia. In terms of mortality due to COVID-19, Indonesia ranks third in Asia and ranks first in Southeast Asia in terms of positive COVID-19 cases. Therefore, technology that can help reduce the spread of COVID-19 by minimizing contact between people. Technology is constantly developing along with increasing human needs. One of them is position tracking. A popular position tracking technology is the Global Positioning System (GPS). But in indoor use, GPS will experience Not Line of Sight (NLOS) due to the complex building structure stands in between the transmitter and receiver. Therefore, a better and more effective indoor position tracking system is needed. In this study, the method used is the Received Signal Strength Indicator (RSSI) from a WiFi router. RSSI is the power received from the transmitter by the receiver. The RSSI value will be inversely proportional to the distance between the transmitter and the receiver. This method utilizes the existing infrastructure, namely router devices that have been installed in various places in the building. We divided the research area into 96 points. We obtain RSSI values from 17 routers for each position and put them into the database. Then the real-time RSSI value will be compared with the RSSI value in the database using the k - Nearest Neighbor algorithm. The webpage displays the position of the user along with their description. The webpage can track and display for up to 5 users. In identifying the crowd, the distance parameter is used to determine the physical identity of the user.