<![CDATA[This study presents the design of a Smart Lecture Room system that utilizes light intensity sensors, specifically CJMCU101. These sensors are installed in each classroom to monitor the ambient conditions. The implementation of the designed system was carried out in the classrooms of the Udayana University Electrical Engineering Study Program. To achieve this goal, the classroom utilized by the Electrical Engineering Study Program of Udayana University was divided into two classes (DH101 and DH102) and a sensor was installed in each class as an IoT device. The IoT devices are connected to a Raspberry Pi Access Point, where the data from the sensors is stored and monitored using the Thinger.io platform. The validation of the sensor testing is carried out by comparing the results obtained from the sensors with the results obtained from a thermohygrometer measurement. This research produces a prototype smart lecture system, applied to a classroom mockup, that employs IoT devices, sensor databases, and sensor monitoring. The data from each sensor's detection is stored in the LAMP database, which employs Linux, Apache, MySQL, and PHP. The Thinger.io platform monitors the values of each sensor. A variation in accuracy between the sensor and measuring instrument results in a difference in their values. The CJMCU101 light intensity sensor has an average accuracy of 93.48% compared to the measuring instrument on DH101. The average accuracy of the sensor value compared to the measuring instrument on DH102 is 95.96%.]]>
