Peramalan Curah Hujan di Kabupaten Tuban Menggunakan Algoritma KNN

Fatimah, Vita
Arifin, Ahmad Zaenal
Putro, Suzatmo

Imajiner: Jurnal Matematika dan Pendidikan Matematika
Vol 7, No 4 (2025): Imajiner: Jurnal Matematika dan Pendidikan Matematika

This study aims to predict rainfall using historical and current data by applying the K-Nearest Neighbors (KNN) method. These predictions are useful for supporting various socio-economic activities, including public safety, agriculture, plantations, fisheries, and aviation. The research method refers to literature studies using data published by the Central Statistics Agency (BPS) of Tuban Regency. The analysis results show an RMSE value of 36.3942 and an R-square of 0.6214 based on 36 monthly data samples covering variables such as temperature, air pressure, wind speed, air humidity, and rainfall.