<![CDATA[Heart rate is one of the health indicators that needs to be paid attention to. With several limitations that occur among the community, such as the availability of equipment and limited knowledge, it means that many people have heart rate abnormalities that are difficult to detect early. This research aims to build a system that can be used anytime and anywhere to monitor and determine heart conditions on an ongoing basis. The system was built using the waterfall method, starting from the analysis stage, data collection, and implementation to the testing stage. This research utilizes Internet of Things technology and the fuzzy logic method to carry out health classification by defining linguistic variables, namely BPM (beats per minute), age, and user activity, and the defuzzification process to obtain heart rate condition classification results. The results of the research show that this monitoring system has been successfully built according to the design stage, namely in the form of an Android application. Testing was carried out on 14 application functionalities, and everything was as expected. This system is also able to measure and transmit heart rate data quickly to the Android application, with a heart rate measurement error of 6.6%. Apart from that, by testing using 10 data samples, the fuzzy logic algorithm was successfully implemented by producing 9 correct classifications and 1 incorrect classification.]]>
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