Aplikasi Prediksi Banjir Dengan Algoritma Spade

IJCIT - Indonesian Journal on Computer and Information Technology

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Field Value
 
Title Aplikasi Prediksi Banjir Dengan Algoritma Spade
 
Creator Ary, Maxsi
 
Subject
 
Description AbstrakPembahasan mengenai prediksi banjir dengan beberapa metode telah dilakukan oleh beberapa penulis. Diantaranya dengan fuzzy logic method, particle swarm optimization algorithms, dan spade algorithms. Tujuan dari penulisan ini adalah membuat aplikasi prediksi banjir dengan algoritma SPADE dari data sample BMKG kota bandung. Early Warning System (EWS) diperlukan untuk informasi awal sistem peringatan dini banjir. Sistem peringatan akan aktif atau menyala jika parameter data yang menjadi data input memenuhi aturan (rule). Program aplikasi menggunakan Microsoft Visual Basic 6.0. Proses input data sebagai informasi prediksi banjir meliputi suhu, kelembaban, kecepatan angina, curah hujan, dan lamanya hujan. Aplikasi prediksi banjir mudah digunakan, hasil yang diberikan yaitu prediksi banjir dan indikator untuk EWS (Early Warning System). Kata Kunci: Algoritma SPADE, Aplikasi Prediksi Banjir, Early Warning System. AbstractThe discussions on flood prediction with several methods have been performed by several authors. Among the fuzzy logic method, particle swarm optimization algorithms, and spade algorithms. The purpose of this paper is to make an application with the flood prediction algorithm SPADE of sample data BMKG Bandung. Early Warning System (EWS) is required to update flood early warning system. Warning system will be activated or lighted if the parameter data into the input data meet the rules (rule). Program applications use Microsoft Visual Basic 6.0. The data input process as flood prediction information includes temperature, humidity, wind speed, rainfall, and duration of the rain. Applications flood prediction is easy to use, the results given that the prediction of floods and indicators for EWS (Early Warning System). Keywords: SPADE Algorithms, Flood Prediction Application, Early Warning System
 
Publisher LPPM Universitas Bina Sarana Informatika
 
Contributor
 
Date 2017-05-29
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artikel yang dipeer-review
 
Format application/pdf
 
Identifier https://ejournal.bsi.ac.id/ejurnal/index.php/ijcit/article/view/1909
10.31294/ijcit.v2i1.1909
 
Source IJCIT; Vol 2, No 1 (2017): Indonesian Journal on Computer and Information Technology
IJCIT (Indonesian Journal on Computer and Information Technology); Vol 2, No 1 (2017): Indonesian Journal on Computer and Information Technology
2549-7421
2527-449X
10.31294/ijcit.v2i1
 
Language ind
 
Relation https://ejournal.bsi.ac.id/ejurnal/index.php/ijcit/article/view/1909/1416
 
Rights ##submission.copyrightStatement##
http://creativecommons.org/licenses/by/4.0
 

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