Visualisasi analisis data DNA Covid-19

DETAIL KOLEKSI

Visualisasi analisis data DNA Covid-19

Oleh : Hafiz Adi Wijaya

Info Katalog

Penerbit : FTI - Usakti

Kota Terbit : Jakarta

Tahun Terbit : 2020

Pembimbing 1 : Syaifudin

Pembimbing 2 : Teddy Siswanto

Subyek : Virus diseases - Covid 19

Kata Kunci : deoxyribonucleic acid (dna), dna sequences data, coronavirus disease 2019 (covid-19), biopython, dat

Status Posting : Published

Status : Lengkap

File Repositori

No.	Nama File	Hal.	Link
1.	2020_TA_SSI_065001600009_Halaman-Judul.pdf
2.	2020_TA_SSI_065001600009_Lembar-Pengesahan.pdf
3.	2020_TA_SSI_065001600009_Bab-1_Pendahuluan.pdf
4.	2020_TA_SSI_065001600009_Bab-2_Tinjauan-Pustaka.pdf
5.	2020_TA_SSI_065001600009_Bab-3_Metodologi-Penelitian.pdf
6.	2020_TA_SSI_065001600009_Bab-4_Analisis-dan-Pembahasan.pdf
7.	2020_TA_SSI_065001600009_Bab-5_Kesimpulan.pdf
8.	2020_TA_SSI_065001600009_Daftar-Pustaka.pdf
9.	2020_TA_SSI_065001600009_Lampiran.pdf

Abstrak
Abstract

S Saat ini sedang terjadi pandemi COVID-19 hampir diseluruh dunia. Perubahan lingkungan baru tempat virus tersebut hidup merupakan salah satu penyebab terjadinya mutasi genetik. Diduga pada masa pandemi ini virus COVID-19 sudah mengalami mutasi genetik. mutasi genetik pada makhluk hidup dapat diidentifikasi menggunakan DNA (Deoxyribonucleic acid) nya. Penelitian ini bertujuan untuk menganalisis DNA Sequences dari data DNA COVID-19 untuk dapat mengidentifikasi mutasi genetik pada sample data yang diuji. Pengumpulan sample data berdasarkan kriteria lokasi awal yang menjadi pusat epidemi, serta lokasi yang menjadi sentral pandemi. Menggunakan metode Data Analysis Process, sequence dari sample data DNA COVID-19 dianalisis informasinya serta divisualisasikan menggunakan library biopython dan matplotlib pada bahasa pemrograman python. Tahapan metode Data Analysis Process meliputi Data Extraction, Data Preparation, Data Exploration & Visualization, Predictive Modeling, Model Validation, dan Deploy. Hasil analisis data berupa urutan nukleotida, sequence alignment yang divisualisasikan, hasil persentase similaritas sequence matching, serta pohon filogenetik. Hasil ini digunakan untuk mengetahui seberapa jauh mutasi genetik terjadi antara sample data DNA COVID-19 yang diuji.

C Currently there is a COVID-19 pandemic in almost all parts of the world. Changes in the new environment in which the virus lives is one of the causes of genetic mutations. It is suspected that during this pandemic the COVID-19 virus had undergone a genetic mutation. genetic mutations in living things can be identified using their DNA (Deoxyribonucleic acid). This study aims to analyze DNA sequences from COVID-19 DNA data to be able to identify genetic mutations in the data samples tested. Collecting data samples based on the criteria for the initial location at the center of the epidemic, as well as the location at the center of the pandemic. Using the Data Analysis Process method, the information sequence from the DNA COVID-19 data sample is analyzed and visualized using the biopython and matplotlib libraries in the python programming language. The stages of the Data Analysis Process method include Data Extraction, Data Preparation, Data Exploration & Visualization, Predictive Modeling, Model Validation, and Deploy. The results of data analysis were in the form of nucleotide sequences, visualized sequence alignment, sequence matching percentage results, and phylogenetic trees. These results are used to determine how far the genetic mutation occurred between the COVID-19 DNA data samples tested.