Prediksi Curah Hujan Menggunakan Long Short Term Memory

Jamilatul Badriyah (Politeknik Elektronika Negeri Surabaya, Surabaya)
Arna Fariza (Politeknik Elektronika Negeri Surabaya, Surabaya)
Tri Harsono (Politeknik Elektronika Negeri Surabaya, Surabaya)

JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 6, No 3 (2022): Juli 2022

The importance of predicting rainfall in fields that require rainfall information such as in agriculture, transportation and industry. Prediction of rainfall with statistics is done to solve the problems of this paper, thus this paper proposes prediction of rainfall using Long Short Term Memory in the case study: Surabaya City. The data used is rainfall data at two Surabaya stations, namely the Perak Meteorological Station I and the Tanjung Perak Maritime Meteorology Station from 2015 to 2020. The prediction test was carried out using the Long Short Term Memory algorithm with accuracy measurement results MSE 0.489, MAE 0.537 and R2 0.497. from these results prove that the Long Short Term Memory algorithm is better than previous studies.