PENGGUNAAN DUAL RESPONSE DENGAN JARINGAN SYARAF TIRUAN UNTUK MANAJEMEN SISTEM KEBENCANAAN DI KOTA MANADO - I Wayan Sukadarminta; Trytia Arungpadang; Johan S C Neyland (JURNAL POROS TEKNIK MESIN UNSRAT, 2019)
This study aims to (1) create artificial neural network architecture and programming using matlab, (2) predict rainfall values for several periods future, and (3) make disaster management systems simple to anticipate disasters.Data were trained and tested to recognize patterns, then simulated to get predictive results. Rainfall data for the past 24 months, from the North Minahasa Climatology Station.The results showed that the function used was trainlm with network architecture 12-8-3-2 and predicted rainfall for the next 12 months (October 2018-September 2019) was 110±1.6106, 267±2.2641, 337±2.7191, 366±2.6943 , 337±2.7853, 305±73.9830, 190±74.4540, 33±70.8810, 34±2.0987, 35±1.3790, 39±1.2715, 68mm±1.3873. The highest rainfall prediction is February 2019 and is predicted to cause flooding. So, a simple disaster management system model is created with the aim of anticipating through activities to avoid and minimize the impact of disasters caused.Keywords: Artificial Neural Networks, Disaster Management, Dual Response,       Floods, Prediction, Rainfall