Drought forecasting using ANFIS on tuban regency, Indonesia

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Andreas Nugroho Sihananto, M. Shochibul Burhan, Arief Andy Soebroto, Wayan Firdaus Mahmudy, Fatwa Ramdani, Ahmad Luthfi, H. Hartanto

2017 Proceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017 Vol. 2018-January Conference paper Cited by 2 Quartile

Abstract

Tuban is a regency on East Java Province, Indonesia that always suffers from drought every year. A forecasting model is being needed to predict when the drought periods will happen next years. This paper studied the forecasting implementation by using two algorithms: Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) with implementation of additional weather parameters such as meridional wind and zonal wind that, as long as authors know, rarely to be used in weather forecasting model. Based on the RMSE test, ANN resulted in RMSE 0.09145; 0.1288; and 0.1194 on three different regions while ANFIS resulted RMSE 0.01733; 0.01645; and 0.01714 on the exact same three regions with ANN. © 2017 IEEE.

Affiliations

Faculty of Computer Science, Universitas Brawijaya, Malang, East Java, Indonesia; Meteorological, Climatological, and Geophysical Agency (BMKG), Karangploso Station, Malang, East Java, Indonesia