PREDIKSI CURAH HUJAN DI KOTA PEKANBARU MENGGUNAKAN METODE JARINGAN SARAF TIRUAN PROPAGASI BALIK

Abstract

Pekanbaru City is a city with a tropical climate with a minimum air temperature of20.2ºC-23.0ºC and a maximum of 34.1ºC-35.6ºC and precipitation of 38.6- 435.0mm/year with the average rainy season from September until April. A prediction of precipitation is required to avoid the impact caused by the high precipitation. This research aims to predict the precipitation period of Pekanbaru City from 2016 until 2020 using the Back Propagation Neural Network method. The data evaluated in monthly data such as precipitation, wind speed, air temperature, humidity, air pressure, and duration of sunlight. This method uses the Matlab R2018a program for programming data and Microsoft Excel for evaluating data and grouping data respectively. The architecture used is composed of 5 input layers using the logsig activation function, 5 hidden layers using the logsig activation function, and 1 output layer using the purelin function. This study divides the data into two parts, i.e., from 2016 until 2019 as training data and from 2020 as a test. The resultsfor the CGB train network training produced the smallest MSE value of 0.00015336 and the network testing produced the best precipitation prediction in February with an error of 0.99736598% where the precipitation was 163.63201mm and the precipitation data was BMKG 162mm.