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http://repository.ipb.ac.id/handle/123456789/110427Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Kusuma, Wisnu Ananta | - |
| dc.contributor.author | Putra, Ryvan Arnandha | - |
| dc.date.accessioned | 2022-01-02T13:09:21Z | - |
| dc.date.available | 2022-01-02T13:09:21Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/110427 | - |
| dc.description.abstract | Komorbid merupakan penyakit tambahan baik fisik maupun psikis selain dari kondisi utama pasien yang dapat memperburuk kondisi pasien. Penyakit komorbid pada pasien covid-19 menjadi salah satu penyebab meningkatnya angka kematian. Pencarian penyakit komorbid covid-19 bertujuan untuk membantu tenaga medis khususnya dalam menangani pasien positif covid-19. Tentunya akan berbeda dalam penanganan apabila pasien dengan penyakit komorbid dengan yang tidak. Penyakit komorbid yang dominan dicari dengan melakukan ekstraksi anotasi abstrak Pubmed terkait covid-19 lalu ditampilkan dalam word cloud berdasarkan frekuensi kemunculannya. Hasil analisis istilah penyakit comorbid dalam word cloud akan dihitung skor Disease Ontology-nya untuk kemudian dibuatkan suatu network. Nilai centrality dalam network yang terbesar akan menunjukkan penyakit komorbid dominan pada covid-19. | id |
| dc.description.abstract | Comorbid is a coexisting disease that can be both physical and psychological apart from the patient's condition which can worsen the medical status. Comorbidity in covid-19 can increase the mortality rate of the patients. The research on covid-19 with comorbidity aims to help medical personnel in dealing with positive covid-19 patients, due to its different treatment for those who have comorbid and those who are not. The present comorbid disease was searched by extracting annotation abstracts regarding covid-19 in Pubmed and then displayed in the Word Cloud based on the frequency appearance. The results of the term comorbid analysis using word-cloud were calculated based on the Disease Ontology and then made the network. The largest value of centrality in network will indicate the dominant comorbid disease in COVID-19. | id |
| dc.language.iso | id | id |
| dc.publisher | IPB University | id |
| dc.title | Analisis Jejaring Penyakit untuk Identifikasi Penyakit Komorbid Dominan Terkait Covid-19 | id |
| dc.type | Undergraduate Thesis | id |
| dc.subject.keyword | covid-19 | id |
| dc.subject.keyword | disease ontology | id |
| dc.subject.keyword | pubmed | id |
| dc.subject.keyword | comorbid | id |
| dc.subject.keyword | wordcloud analyst | id |
| Appears in Collections: | UT - Computer Science | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Cover, Lembar Pengesahan, Prakata, Daftar Isi.pdf Restricted Access | Cover | 352.88 kB | Adobe PDF | View/Open |
| G64170007_Ryvan Arnandha Putra.pdf Restricted Access | Fulltext | 1.49 MB | Adobe PDF | View/Open |
| Lampiran.pdf Restricted Access | Lampiran | 413.98 kB | Adobe PDF | View/Open |
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