Prediksi Curah Hujan Wilayah Provinsi Yogyakarta dengan Algoritma Neural Network
DOI:
https://doi.org/10.26905/jasiek.v3i1.6204Keywords:
Prediksi, Curah hujan, Neural networkAbstract
Emerging inaccurate information about the rainfall system can affect aspects of life. Inaccurate precipitation forecasting can be problematic, so it is necessary to predict precipitation with a high level of accuracy. Therefore, this study proposes a method with a neural network algorithm to predict rainfall to benefit the community. The data used in this study is daily precipitation from 2016 to 2021 from BMKG. Based on the test results, the data shows that the best neural network (NN) model is obtained from input layer 31, hidden layer 4, training cycle 1500, learning rate 0.01, and momentum 0.9, resulting in an error of 0.828. Based on the results with the smallest error, using the neural network method can be used to predict future precipitation with good accuracy.
References
Damar A P, Ahmad Z, Sumiharni. Studi Pemodelan Curah hujan sintetik dari beberapa stasiun di wilayah Pringsewu. JRSDD. 2015;3 (1): 45-56.
Sutopo P N. Evaluasi dan analisis curah hujan sebagai faktor Penyebab bencana banjir jakarta. Jurnal Sains & Teknologi Modifikasi Cuaca. 2002; 3 (2):91-97.
Dedi, M. Analisis Karakteristik Curah Hujan di Wilayah Kabupaten Garut Selatan. Jurnal Konstruksi. vol. 2014;13 (1):2302-7312.
Sitti H, Usman. Analisa Prediktif Curah Hujan Data Time Series Berbasis Metode Neural Network. Teknologi Informasi dan Komunikasi. 2020; 10 (2): 163-176.
M Muflih, Nur A, Wagino. Prakiraan Curah Hujan Bandara Syamsudin Noor dengan Algoritma Neural Network Backpropagation. Technologia. 2017; 8 (1).
Yuli A, Hotmalina S, Anjar W. Analisis Jaringan Syaraf Tiruan untuk prediksi volume ekspor dan impor migas di Indonesia. Ilmiah Teknologi Sistem Informasi. 2018; 4: 30-40.
Asep K H, Empung. Analisis curah hujan efektif dan curah hujan dengan berbagai periode ulang untuk Wilayah Kota Tasikmalaya dan Kabupaten Garut. Siliwangi 2016; 2 (2): 2477-3891.
Yudhi A, Erlinda N. Prediksi Curah Hujan Di Kota Medan Menggunakan Metode Backpropagation Neural Network. Seminar Nasional Informatika. 2014.
Rama D S. Performa Algoritma User K-Nearest Neighbors pada Sistem Rekomendasi di Tokopedia. Jurnal Informatika Universitas Pamulang. 2020; 5 (3): 302–306.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
The journal allow the authors to hold the copyright without restrictions and allow the authors to retain publishing rights without restrictions.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
