Prediksi Curah Hujan Menggunakan Long Short Term Memory

  • Badriyah J
  • Fariza A
  • Harsono T
N/ACitations
Citations of this article
96Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Badriyah, J., Fariza, A., & Harsono, T. (2022). Prediksi Curah Hujan Menggunakan Long Short Term Memory. JURNAL MEDIA INFORMATIKA BUDIDARMA, 6(3), 1297. https://doi.org/10.30865/mib.v6i3.4008

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free