MACHINE LEARNING PREDIKSI CUACA DENGAN DATA RECORD ALGORITMA K-NN DI WILAYAH DESA PLANCUNGAN

Agriculture as one of the industrial sectors is part of society, both as a livelihood, supporting development, and a high absorber of manpower. Superior products from agriculture, for example tobacco. Plancungan Village is a tobacco-producing village. Farmers cultivate chopped tobacco like Virginia tobacco. Changing and erratic weather can affect crop yields, moreover drying is done in the open and takes 2 to 3 days. This makes the weather one of the determining factors during the tobacco drying process. This research will implement the K-Nearest Neighbor (K-NN) machine learning algorithm in predicting the weather in the Plancungan Village area, so that farmers can find out information early on and make countermeasures if necessary. The data taken using a microcontroller is installed in the village of Plancungan, which then the device will record temperature, humidity and pressure conditions. For the dataset and training data, 2,500 data were used from the 10,000 existing data. The results of this study are in the form of information on weather conditions in the form of rainy, sunny and cloudy in the Plancungan Village area in the form of a web page display.