Please use this identifier to cite or link to this item: 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 SizeFormat 
Cover.pdf
  Restricted Access
Cover2.6 MBAdobe PDFView/Open
Fullteks.pdf
  Restricted Access
Fullteks7.55 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.