View Item 
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Physics
      • View Item
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Physics
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Pemodelan Berbasis Agen Dinamika Infeksi Virus SARS-CoV-2 dan Efek Vaksinasi

      Thumbnail
      View/Open
      Cover (489.0Kb)
      Fullteks (932.1Kb)
      Lampiran (243.2Kb)
      Date
      2022
      Author
      Kurniasih, Anisa
      Alatas, Husin
      Hardhienata, Hendradi
      Metadata
      Show full item record
      Abstract
      Salah satu virus yang menjadi penyebab pandemi COVID-19 dalam beberapa tahun terakhir yaitu SARS-CoV-2. Penelitian ini memodelkan interaksi antibodi, sel darah putih, sel epitel, vaksin COVID-19 dan virus SARS-CoV-2 menggunakan pemodelan berbasis agen. Pemodelan berbasis agen digunakan untuk simulasi suatu sistem yang kompleks sesuai aturan-aturan dalam fenomena nyata yang terjadi di alam. Seluruh agen memiliki aturan yang didasarkan dari karakteristik dan perilaku setiap agen ketika berinteraksi didalam tubuh. Simulasi dilakukan dengan enam skenario dan satu skenario tambahan. Setiap skenario dibedakan dengan waktu ketika virus mulai menginfeksi. Hasil simulasi menunjukkan bahwa virus yang menginfeksi setelah pemberian vaksin dosis lanjutan (booster) dapat di tangani antibodi dengan optimal dibandingkan sebelum pemberian vaksin primer dosis lengkap. Pada simulasi jangka panjang untuk skenario tambahan menunjukkan bahwa diperlukan vaksin dosis keempat untuk mempertahankan efektivitas vaksin. Virus yang berinteraksi dengan sel epitel dan melakukan infeksi-replikasi akan meningkatkan nilai entropi. Nilai entropi akan menurun apabila virus dapat ditangani dengan baik oleh antibodi.
       
      One of the viruses that caused the COVID-19 pandemic in the last few years is SARS-CoV-2. This study modeled the interaction of antibodies, white blood cells, epithelial cells, SARS-CoV-2 virus and COVID-19 vaccine by using the agent based modeling. The agent-based modeling is applied to simulate a complex system based on the rules in real phenomena which occur in nature. All of the agents have rules that are based on the characteristics and behaviour of each agent when interacting inside the body. The simulation was done in six scenarios and one additional scenario. Each scenario was distinguished by the time when the virus started to infect. The result of the simulation showed that the virus that was infected after the giving of the booster dose vaccine could be handled more optimally than the previous giving of the primary dose vaccine. Long term simulations for additional scenarios indicated that there was a need for a fourth dose vaccine dose to maintain the effectiveness of the vaccine. Viruses that interacted with the epithel cell and did a replicate-infection would increase the total entropy value, the entropy value would decrease if the virus could be handled properly by the antibodies.
       
      URI
      http://repository.ipb.ac.id/handle/123456789/115167
      Collections
      • UT - Physics [848]

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository
        

       

      Browse

      All of IPB RepositoryCollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

      My Account

      Login

      Application

      google store

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository