Implementasi Jaringan Syaraf Tiruan dalam Memprediksi Hujan

Information technology is a technology used to manage data, including processing, acquiring, organizing, storing, and manipulating data in various ways to produce high-quality information—namely, information that is relevant, accurate, and timely. This information is used for personal, business, and governmental purposes, serving as strategic information in decision-making. To anticipate changes in weather conditions, particularly rainfall, a valid and accurate report is needed that can be useful for the public. So far, the correlation or relationship between the factors influencing weather conditions—especially rainfall—has not been precisely determined, making it mathematically difficult to create a model that can describe the correlation among all these factors. This is where Artificial Neural Networks (ANN) come into play: to create such models and map out the existing problems purely based on the input data provided. One of the capabilities of neural networks is to make predictions based on previously learned data using the backpropagation method.

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Publication Details

Journal
Elkom Jurnal Elektronika dan Komputer
Published
2025-07-30
DOI
https://doi.org/10.51903/elkom.v18i1.2986
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

Implementasi Jaringan Syaraf Tiruan dalam Memprediksi Hujan

Silvia Ningsih
Elkom Jurnal Elektronika dan Komputer
Data Mining and Machine Learning Applications
article

Implementasi Jaringan Syaraf Tiruan dalam Memprediksi Hujan

Silvia Ningsih
article en

Abstract

Information technology is a technology used to manage data, including processing, acquiring, organizing, storing, and manipulating data in various ways to produce high-quality information—namely, information that is relevant, accurate, and timely. This information is used for personal, business, and governmental purposes, serving as strategic information in decision-making. To anticipate changes in weather conditions, particularly rainfall, a valid and accurate report is needed that can be useful for the public. So far, the correlation or relationship between the factors influencing weather conditions—especially rainfall—has not been precisely determined, making it mathematically difficult to create a model that can describe the correlation among all these factors. This is where Artificial Neural Networks (ANN) come into play: to create such models and map out the existing problems purely based on the input data provided. One of the capabilities of neural networks is to make predictions based on previously learned data using the backpropagation method.

Elkom Jurnal Elektronika dan KomputerVol. 18(1)
Openalex Percentile: Top 72%
Data Mining and Machine Learning Applications
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Implementasi Jaringan Syaraf Tiruan dalam Memprediksi Hujan — Silvia Ningsih · Elkom Jurnal Elektronika dan Komputer (2025) | TGRS Research Map | TGRS