<![CDATA[Vehicle technicians in checking the condition of the car's engine mounting do it manually, namely, through sight and hearing. This kind of manual method often makes an error in diagnosing engine mounting damage, because each individual has a different level of hearing and vision sensitivity. This research aims to make it easier for technicians to check the feasibility level of engine mounting with accurate data. This tool is based on IoT technology, where the reading of graphs from sensors in analyzing engine mounting damage using a website display and a 20 x 4 LCD. For its data storage with MySQL Database. In its working principle, it uses the K-Nearest Neighbor (KNN) algorithm method, in order to distinguish between engine mounting that is still good and damaged. Graph readings based on normal and abnormal range data from the data retrieval of the engine mounting of the new unit car. The vibration sensor used is the ADXL345 and also several other sensors such as the temperature sensor (MLX90614) and the sound sensor (KY-037). It uses the Arduino UNO R3 microcontroller and the Esp8266 NodeMCU as a data sender to the server. Tests were carried out on cars in idling conditions of 1000-1300 rpm. From the results of the study produced standard feasibility for vibrations from 3 axes (x = 1.60 ; y = 1.60 ; z = 1.90), temperature = 30 °C, Sound = 71 dB.]]>
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