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All Journal Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Indah Ramadhani
Universitas Samudra

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Penerapan Backpropagation Neural Network pada Prediksi Curah Hujan di Sumatera Utara Ulya Nabila; Indah Ramadhani; Fazrina Saumi
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 4 No 1 (2023): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v4i1.10503

Abstract

Indonesia is located on the equator with a latitude of 6°N to 11°S. This latitude causes a high intensity of solar radiation so that the air temperature becomes high. This causes the evaporation of water from the surface of the sea and land to form clouds and rain. One of the provinces in Indonesia that has high rainfall is North Sumatera. Due to the high rainfall, the province often experiences floods and landslides. In order to minimize the impact of floods and landslides, the first thing that can be done is to predict the rainfall in North Sumatera. The method used is Backpropagation Neural Network. This method is a kind of artificial intelligence designed to process information by imitating the nervous system of the human brain. This research aimed to predict rainfall in North Sumatera using Backpropagation Neural Network and determine the accuracy of this method. The data came from the Badan Pusat Statistik (BPS) of North Sumatera, namely rainfall data from January 2020 to December 2022. The results implied that rainfall in 2023 for each month is 190; 266; 197; 178; 290; 182; 299; 350; 213; 485; 357; and 389 (mm/month) and has an accuracy of Mean Absolute Percentage Error (MAPE) of 35.55%, so this method is categorized as suitable for predicting rainfall.
Co-Authors Fazrina Saumi Ulya Nabila