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All Journal Jurnal Sistem Informasi dan Ilmu Komputer Kohesi: Jurnal Sains dan Teknologi Jurnal Penelitian Teknologi Informasi dan Sains Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer
Arizka Anggraini
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Education Energy Engineering Other

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Journal : Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer

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Pemanfaatan Jaringan Saraf Tiruan untuk Prediksi Curah Hujan di Sumatera Utara Arizka Anggraini; Lailan Sofinah Harahap
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.457

Abstract

The use of Artificial Neural Networks (JST) for weather prediction is one of the innovative approaches in climate data analysis. This study aims to apply JST in predicting weather, especially rainfall and the number of rainy days in the North Sumatra region. Historical weather data obtained from BMKG Region I for 2022-2023 is used as input to train the JST model. With a training process that involves processing rainfall data, this model is expected to provide accurate predictions regarding weather patterns. The results of this research can help in agricultural sector planning, disaster risk mitigation, and natural resource management. JST has proven to be effective in identifying dynamic and complex weather patterns, so it has the potential to be used in long-term weather prediction.
Co-Authors Adisty Maysandra Armansyah Armansyah Lailan Sofinah Harahap Latifa Khoirani Nazwa Alya Faradita Supiyandi Supiyandi Warda Hamidah