<![CDATA[Weather is one of the important parts that occur in human life. The fields of human occupation that are most affected by the weather, for example, are agriculture, tourism, transportation, and also other fields that require outdoor activities. Before working, humans will see the weather forecast through various media such as weather applications. When entering the rainy season, the weather in Indonesia cannot be predicted accurately even though it has been forecasted, because the weather in Indonesia during the rainy season can change. Currently, Indonesia has used the AWS system but it is still in limited numbers which is also because the AWS used is still made by another country, so it has a fairly expensive price. Therefore, this study will design and implement an Internet of Things-based Weather Monitoring System using the Naïve Bayes algorithm that can help classify the weather status where the device is located. The device is built using DHT11 sensors, LDR, and rain gauge sensors as input parameters for weather data. Based on the tests that have been carried out, the system that has been built can run well. All the features created can function properly and can display weather results according to the Naïve Bayes algorithm calculations. The tool that was built can receive data and send data into the database. The application that was built can implement the Naïve Bayes algorithm and has an average accuracy of 92.49%.]]>
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