K-Nearest Neighbor (KNN) Method for Weather Data Prediction

Penerapan Metode K-Nearest Neighbour (KNN) Untuk Prediksi Data Cuaca

Abstract

The weather tends to change frequently every day, so weather forecasts are made to be used as an early warning if sudden weather changes occur. By forecasting the weather, losses can be minimized and people are alert to carry out outdoor activities. From this problem, the K-Nearest Neighbor (KNN) method was applied. This method is expected to provide accurate and efficient information to obtain weather predictions for existing conditions. The data used is secondary data. After conducting research on training data (old data) amounting to 80% and test data (new data) amounting to 20%. The accuracy results from the testing data predictions are 75% with a value of k = 8.