Aplikasi Pemetaan Penyakit Demam Berdarah di Surabaya dengan Metode Neural Network Multilayer Perceptron

Ivan Enrico Widodo, Andreas Handojo, Siana Halim

Abstract


Dengue fever is a disease that caused by dengue virus. This virus is transmitted into human body through mosquito bites, aedes aegypti and aedes albopictus. This kind of mosquito are mostly found in subtropical and tropical regions, including in Indonesia. Almost every year, cases of dengue fever occur in Indonesia. Government’s effort to prevent dengue fever have been carried out. Following the development of technology, the government began to save patient data through their own health institution, the community health centers.

However, the stored data cannot produce useful information instantly. The data must go through series of processes first before it can become informastion. Data processing methods that can be used are neural network. Because neural network have one function that is prediction. Then, the prediction data can be entered into a digital map for the mapping process. Mapping with digital map that have colors and display the level of sufferers can be said to produce useful information.

 The result of this program is a website that can display maps in the form of digital map, with data obtained based on prediction results using neural network method. So that later this website can help the government to take preventive measures againts dengue fever.

Keywords


Neural Network; Digital Map; Dengue Fever; Prediction

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References


Baihaqi, A. 2019, Februari 01. Sebulan, Penderita Demam Berdarah di Surabaya 23 Orang. URI = https://news.detik.com/berita-jawa-timur/d-4410367/sebulan-penderita-demam-berdarah-di-surabaya-23-orang

Depkes. 2017. Demam Berdarah Dengue. URI = http://www.depkes.go.id/development/site/depkes/index.php?cid=1-17042500004&id=demam-berdarah-dengue-dbd-.html.

Google LLC. 2019. GoogleMaps Platform Documentation. URI = https://developers.google.com/maps/documentation/.

Jongmuenwai, B., Lowanichchai, S., & Jabjone, S. 2018. Prediction Model of Dengue Hemorrhagic Fever Outbreak using Artificial Neural Networks in Northeast of Thailand. International Journal of Pure and Applied Mathematics Volume 118, (hal. 3407-3417).

Krisnadi I., Rakhmatsyah A., & Wirayuda T. A. B. 2008. Perbandingan Antara Jaringan Syaraf Tiruan Multilayer Perceptron Dan Jaringan Syaraf Tiruan Multilayer Perceptron – Tabu Search (Studi Kasus: Klasifikasi Bunga Iris). (Undergradate Thesis). URI = https://repository.telkomuniversity.ac.id/.

Laureano-Rosario, A., Duncan, A., Mendez-Lazaro, P., Garcia-Rejon, J., Gomez-Carro, S., Farfan-Ale, J., ... & Muller-Karger, F. 2018. Application of artificial neural networks for dengue fever outbreak predictions in the northwest coast of Yucatan, Mexico and San Juan, Puerto Rico. Tropical medicine and infectious disease, 3(1), 5.

Mollalo, A., Mao, L., Rashidi, P., & Glass, G. E. 2019. A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States. International journal of environmental research and public health, 16(1), 157.

Prathama, A. Y., Aminullah A., & Saputra A. 2017. Pendekatan ANN (Artificial Neural Network) Untuk Penentuan Prosentase Bobot Pekerjaan dan Estimasi Nilai Pekerjaan Struktur pada Rumah Sakit Pratama. 7(1), 1-82. DOI = doi:10.22146/teknosains.30139.

Reisha, T. 2019, February 12. Hingga Februari 2019, Terdapat 13.683 Kasus DBD di Indonesia. URI = https://news.detik.com/berita/d-4425473/hingga-februari-2019-terdapat-13683-kasus-dbd-di-indonesia.

Suhartono, D. 2012. Dasar Pemahaman Neural Network. URI = https://socs.binus.ac.id/2012/07/26/konsep-neural-network/


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