PREDIKSI CURAH HUJAN DAN PENGARUHNYA TERHADAP WABAH DEMAM BERDARAH MENGGUNAKAN PENDEKATAN DEEP LEARNING DI KABUPATEN BANYUMAS

Januwarsa, Rangga Prangwedana (2020) PREDIKSI CURAH HUJAN DAN PENGARUHNYA TERHADAP WABAH DEMAM BERDARAH MENGGUNAKAN PENDEKATAN DEEP LEARNING DI KABUPATEN BANYUMAS. Other thesis, Universitas Amikom Purwokerto.

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Abstract

Dengue fever is a disease whose spread cases always occur every year. This disease is very dangerous if handled late. Seeing how dangerous dengue fever is, of course it neede necessary precautions. One way to prevent dengue fever is to predict it. Based on previous research, it was found that rainfall has an influence on the spread of dengue fever. By predicting rainfall, there is a possibility that the number of dengue fever sufferers can also be estimated. The purpose of this study is to make a prediction model for rainfall in Banyumas Regency. In addition to rainfall, this study also aims to predict the spread of dengue outbreaks in Banyumas. To make the prediction model, deep learning approach is used. The results showed that the predicted results of average rainfall in 2019 were 5.6799 mm. The prediction result for the number of dengue fever sufferers in 2019 is 503.0892 for an average rainfall of 15.6399. The highest rainfall itself occurred in 2016 with a figure of 19.4876, and in 2016 there were 990 sufferers. From these results and the data used in general it can be concluded that the high rainfall rate will result in an increased number of dengue fever sufferers.
Item Type: Thesis (Other)
Additional Information: Dosen Pembimbing: Dr. Berlilana, M.Kom., M.Si.
Uncontrolled Keywords: Dengue fever, Rainfall, Python, Prediction, Deep Learning
Subjects: R Medicine > R Medicine (General)
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: UPT Perpustakaan Pusat Universitas Amikom Purwokerto
Date Deposited: 05 Nov 2020 07:40
Last Modified: 05 Nov 2020 07:40
URI: https://eprints.amikompurwokerto.ac.id/id/eprint/362

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