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https://repositori.uma.ac.id/handle/123456789/21314
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DC Field | Value | Language |
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dc.contributor.advisor | Noviandri, Dian | - |
dc.contributor.advisor | Lubis, Andre Hasudungan | - |
dc.contributor.author | Hasibuan, Novita Afrina Sari | - |
dc.date.accessioned | 2023-10-02T08:12:59Z | - |
dc.date.available | 2023-10-02T08:12:59Z | - |
dc.date.issued | 2023-04-14 | - |
dc.identifier.uri | https://repositori.uma.ac.id/handle/123456789/21314 | - |
dc.description | 95 Halaman | en_US |
dc.description.abstract | Penelitian ini bertujuan untuk dapat mempermudah masyarakat dalam mengetahui gejala Covid-19 pada anak sejak dini. Sehingga dibutuhkan cara atau metode lain untuk mengetahui ada atau tidaknya virus tersebut pada diri anak-anak. Masalah difokuskan pada bagaimana mengimplementasikan teorema bayes kedalam sistem pakar untuk deteksi dini Covid-19 pada anak-anak, dengan sampel data diambil dari pasien Covid-19 yang berusia 5-12 tahun di RS Haji Medan berjumlah 80 orang. Guna mendekati masalah ini dipergunakan acuan teori dari dari beberapa studi literatur yang berupa jurnal terkait. Data-data dikumpulkan melalui kegiatan observasi, interview dan dianalisis secara kualitatif. Kajian ini menyimpulkan bahwa hasil perhitungan teorema bayes yang dilakukan memberikan hasil positif karena metode yang digunakan sesuai dengan kebutuhan sistem yang menggunakan nilai densitas dari gejala. Pengujian Sistem Pakar Deteksi Dini Covid-19 Pada Anak dengan menggunakan Teorema Bayes menunjukkan bahwa sistem pakar ini bisa mengindentifikasi kemungkinan bahwa pasien akan terpengaruh Covid-19 sesuai dengan gejala yang di input ke dalam sistem. This research aims to facilitate the community to deal with the symptoms of Covid-19 in children from an early age. This study proposes another method to inspect the virus in children by neglecting the general method. The problem is focused on how to implement Bayes' theorem into an expert system for early detection of Covid-19 in children, with 80 data samples taken from Covid-19 patients aged 5-12 years at Medan Haji Hospital. In order to approach this problem, theoretical references are used from several literature studies in the form of related journals. The data were collected through observation, interviews and analyzed qualitatively. This study concludes that the Bayes' theorem calculation results are positive because the method used is in accordance with the needs of the system that uses the density value of the symptoms. Testing the Expert System for Early Detection of Covid-19 in Children using Bayes' Theorem shows that this expert system can identify the possibility that patients will be affected by Covid-19 according to the symptoms that are input into the system. | en_US |
dc.language.iso | id | en_US |
dc.publisher | Universitas Medan Area | en_US |
dc.relation.ispartofseries | NPM;178160078 | - |
dc.subject | deteksi | en_US |
dc.subject | anak | en_US |
dc.subject | teorema bayes | en_US |
dc.subject | covid-19 | en_US |
dc.subject | sistem pakar | en_US |
dc.subject | detection | en_US |
dc.subject | child | en_US |
dc.subject | bayes theorem | en_US |
dc.subject | covid-19 | en_US |
dc.subject | expert system | en_US |
dc.title | Sistem Pakar Deteksi Dini Covid-19 pada Anak dengan Menggunakan Teorema Bayes | en_US |
dc.title.alternative | Expert System for Early Detection of Covid-19 in Children Using Bayes' Theorem | en_US |
dc.type | Skripsi Sarjana | en_US |
Appears in Collections: | SP - Informatic Engineering |
Files in This Item:
File | Description | Size | Format | |
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178160078 - Novita Afrina Sari Hasibuan - Fulltext.pdf | Cover, Abstract, Chapter I, II, III, V, Bibliography | 1.27 MB | Adobe PDF | View/Open |
178160078 - Novita Afrina Sari Hasibuan - Chapter IV.pdf Restricted Access | Chapter IV | 467.7 kB | Adobe PDF | View/Open Request a copy |
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