CD-ROM
Classification Of Occupant Position Ventilation In The Libarary In The Under Actuated Zone using The K-Nearest Method
Since the pandemic has subsided, various sectors have begun to move in the
new normal era, one of which is the world of education. Universities, especially in
Jakarta, have begun to treat face-to-face activities on campus. One of the campus
facilities that is always used in learning activities is the library. The use of air
circulation must be very considered, one of which is in the Trilogy University
library currently using the HVAC system which is carried out traditionally, Where
to control the room temperature using the buttons located on the walls of the library
and the room temperature does not care about the number of residents in it. Based
on these problems, a system is needed that is able to detect the presence of the
number of people in the library room. The purpose of this study is to be able to
detect the presence of occupants in a room. The method used is K-Nearest
Neighbors. This method uses 90 data provided by a Wifi network sensor (Wireless
Adapter) placed on the room vent to capture the value on each Access Point (AP),
the value captured is in the form of signal strength in the form of RSSI, Frequency,
and Limit. The results of this study are a system that can work by 94% with an error
value of 0.05 and for retesting data, validation is carried out with 15 direct data with
a result of 15/15, which is 100% accuracy. This research shows that this system is
able to detect residents in a room well, besides that the system is also able to test
real data.
Keywords: Internet of Things, Occupant, K-Nearest Neighbor, HVAC, Sensor
TI23/001 | TI23/001 | Prodi Teknik Informatika | Tersedia |
Tidak tersedia versi lain