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http://repository.ipb.ac.id/handle/123456789/108854
Title: | Model Prediksi Jumlah Kasus COVID-19 dan Analisis Berbasis Demografi, Sosial dan Ekonomi Menggunakan Long Short Term Memory (Studi Kasus di Jawa Timur) |
Other Titles: | Prediction Model Number of COVID-19 Cases and Analysis Based on Demography, Social and Economy Using Long Short Term Memory (Case Study: East Java Province) |
Authors: | Herdiyeni, Yeni Hardhienata, Medria Kusuma Dewi Putri, Avrienta Nouva Eka |
Issue Date: | Aug-2021 |
Publisher: | IPB University |
Abstract: | Coronavirus Disease 2019 atau (COVID-19) disebabkan oleh jenis virus
corona baru yang dapat menimbulkan penyakit pernapasan. Penyakit ini
ditemukan pertama kali di Wuhan, China, pada bulan Desember 2019. Virus ini
ditularkan melalui cairan atau kontak langsung dan menginfeksi saluran
pernapasan yang mengakibatkan pneumonia di sebagian besar kasus. Faktor
demografi, sosial dan ekonomi merupakan faktor-faktor yang mendorong
penyebaran penyakit menular. Antisipasi dan pengukuran dari berbagai faktor
yang terlibat dalam penyakit menular dapat dimodelkan secara matematis dengan
pemodelan matematika. Penelitian ini melakukan pemodelan prediksi kasus
COVID-19 di Jawa Timur menggunakan Long Short Term Memory (LSTM).
Berdasarkan hasil penelitian, kabupaten/kota di Jawa Timur terbagi menjadi lima
cluster sesuai karakteristik demografi, sosial dan ekonominya. Jumlah kasus
positif COVID-19 yang tinggi terdapat di cluster dengan PDRB yang tinggi. Hasil
analisis regresi menunjukan bahwa atribut PDRB merupakan atribut yang
berpengaruh signifikan terhadap jumlah terkonfirmasi COVID-19 di Jawa Timur.
Penelitian ini memperkirakan jumlah terkonfirmasi positif COVID-19 masih terus
naik hingga akhir Juli 2021. Coronavirus Disease 2019 or (COVID-19) is caused by a new type of coronavirus that can cause respiratory disease. This disease was first discovered in Wuhan, China, in December 2019. This virus is transmitted through fluids or direct contact and infects the respiratory tract resulting in pneumonia in most cases . Demographic, social and economic factors are factors that encourage the spread of infectious diseases. The anticipation and measurement of various factors involved in infectious diseases can be modeled mathematically. This research conducts predictive modeling of COVID-19 cases in East Java using Long Short Term Memory (LSTM). Based on the research results, districts/cities in East Java are divided into five clusters according to their demographic, social and economic characteristics. Many positive cases of COVID-19 are found in clusters with a high value of Gross Regional Domestic Product (GDP regional). The results of the regression analysis indicate that GDP regional attribute is an attribute that has a significant effect on the number of positive confirmed cases of COVID-19 in East Java. This study estimates that the addition of the positive number of COVID-19 will continue to rise until the end of July 2021. |
URI: | http://repository.ipb.ac.id/handle/123456789/108854 |
Appears in Collections: | UT - Computer Science |
Files in This Item:
File | Description | Size | Format | |
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Cover.pdf Restricted Access | Cover | 2.6 MB | Adobe PDF | View/Open |
Fullteks.pdf Restricted Access | Fullteks | 7.55 MB | Adobe PDF | View/Open |
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