Analisa Visualisasi Data Covid – 19 Di Indonesia Menggunakan Tableau Big Data
- Prayoga Pangestu STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Dedy Hartama STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Dedi Suhendro STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Abdi Rahim Damanik STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
-
Selli Oktaviani
*
STIKOM Tunas Bangsa, Pematangsiantar,
Indonesia
(*) Corresponding Author
Abstract
This study explains the benefits of data analysis by visualization of Big data inoptimizing cases of the spread of COVID-19 in Indonesia. The data used is the COVID-19 Indonesia time series data from the Kaggle website. In this study, the author used tableau tools to analyze data based on worksheets of covid-19 distribution maps, COVID-19 statistics, details of active cases per province, death cases per province, active cases, death cases, confirmed cases and produced a dashboard of COVID-19 data. The results of the analysis obtained using visualizations in the form of graphs are very fast and optimize data processing so that they can find out which provinces are affected by active cases and deaths of COVID-19 from the highest to the lowest in Indonesia and can be used in decision and policy making for the Indonesian government.
Downloads
References
J. J. Inkiriwang and F. N. P. W. Waworundeng, “Kinerja Pemerintah Dalam Penanganan Pandemi Covid-19 Di Kecamatan Wanea Kota Manado,” vol. 3, no. 2, pp. 1–23, 2023.
Kemenkes, “Rencana Strategis Kementerian Kesehatan Tahun 2020-2024,” Kaos GL Derg., vol. 8, no. 75, pp. 147–154, 2020, [Online]. Available: https://doi.org/10.1016/j.jnc.2020.125798%0Ahttps://doi.org/10.1016/j.smr.2020.02.002%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/810049%0Ahttp://doi.wiley.com/10.1002/anie.197505391%0Ahttp://www.sciencedirect.com/science/article/pii/B9780857090409500205%0Ahttp:
N. Rahmiati, Afrianti, “Faktor-Faktor Yang Mempengaruhi Kepatuhan Masyarakat Terhadap Protokol Kesehatan Covid-19,” J. Ilm. STIKES Kendal, vol. 11, no. 1, pp. 113–124, 2021, [Online]. Available: https://journal.stikeskendal.ac.id/index.php/PSKM/article/view/1045/647
D. Saepuloh, “Visualisasi Data Covid 19 Provinsi DKI Menggunakan Tableau,” J. Ris. Jakarta, vol. 13, no. 2, pp. 55–64, 2020, doi: 10.37439/jurnaldrd.v13i2.37.
H. Wiguna, Y. Nugraha, F. Rizka R, A. Andika, J. I. Kanggrawan, and A. L. Suherman, “Kebijakan Berbasis Data: Analisis dan Prediksi Penyebaran COVID-19 di Jakarta dengan Metode Autoregressive Integrated Moving Average (ARIMA),” J. Sist. Cerdas, vol. 3, no. 2, pp. 74–83, 2020, doi: 10.37396/jsc.v3i2.76.
R. Pakpahan and Y. Fitriani, “Analisa Pemafaatan Teknologi Informasi Dalam Pemeblajaran Jarak Jauh Di Tengah Pandemi Virus Corona Covid-19,” JISAMAR (Journal Inf. Syst. Applied, Manag. Account. Researh), vol. 4, no. 2, pp. 30–36, 2020.
R. N. Putri, “Indonesia dalam Menghadapi Pandemi Covid-19,” J. Ilm. Univ. Batanghari Jambi, vol. 20, no. 2, p. 705, 2020, doi: 10.33087/jiubj.v20i2.1010.
S. Siska and D. S. Putri, “Implementasi Business Intelligence Untuk Menganalisis Perbandingan Data Kasus Covid-19 Di Jawa Barat Sebelum Psbb Dan Setelah Psbb,” Edutic - Sci. J. Informatics Educ., vol. 7, no. 2, 2021, doi: 10.21107/edutic.v7i2.9893.
I. Y. Arulampalam Kunaraj, P.Chelvanathan, Ahmad AA Bakar, “Penerapan Bussiness Intelligence untuk Menganalisis Data Kasus Covid 19 Di Provinsi Jawa Barat Menggunakan Platform Google Data Studio,” J. Eng. Res., vol. 22, pp. 187–196, 2023.
L. Liliana, D. Vera, A. S. Wijaya, and D. Y. Bernanda, “Penggunaan Big Data Untuk Menganalisis Tingkat Keberhasilan Siswa Menempuh Mata Kuliah,” Pros. Semin. Nas. Teknoka, vol. 4, no. 2502, pp. I77–I82, 2019, doi: 10.22236/teknoka.v4i0.4208.
F. Azizah and U. K. Indonesia, “Penerapan Big Data dalam Bidang Pendidikan Studi Kasus Menganalisa Kinerja Siswa Penerapan Big Data dalam Bidang Pendidikan Studi Kasus Menganalisa Kinerja Siswa,” no. December, 2023.
A. S. Sinaga, “Analisa Big Data Penyebaran Covid-19 Dengan Business Intelligence (Bi),” J. Ilm. Teknol. dan Rekayasa, vol. 26, no. 3, pp. 218–226, 2021, doi: 10.35760/tr.2021.v26i3.4067.
R. M. A. Yogi aditya saputra, syafrial fachri pane, Big Data : Implementasi Hadoop Mapreduce pada pemetaan sekolah menggunakan phyton. Bandung: Kreatif Industri Nusantara, 2020.
A. Setiawan et al., “Visualisasi Data Progres Program Vaksinasi COVID-19 Internasional Berbasis Tableau,” Ilk. J. Comput. Sci. Appl. Informatics, vol. 4, no. 1, pp. 25–33, 2022, doi: 10.28926/ilkomnika.v4i1.441.
A. H. G. Balamurugan Balusamy, Nandhini Abirami R, Big Data: Concepts, Technology and Architecture. John Wiley and Sons, Incorporated, 2021.
D. Hartama, “Analisa Visualisasi Data Akademik Menggunakan Tableau Big Data,” Jurasik (Jurnal Ris. Sist. Inf. dan Tek. Inform., vol. 3, no. 3, p. 46, 2018, doi: 10.30645/jurasik.v3i0.65.
M. Ariandi and S. Rahma Puteri, “Analisis Visualisasi Data Kecamatan Kertapati menggunakan Tableau Public,” JUPITER (Jurnal Penelit. Ilmu dan Tek. Komputer), vol. 14, no. 2-b, pp. 366–373, 2022, [Online]. Available: https://jurnal.polsri.ac.id/index.php/jupiter/article/view/5141
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Analisa Visualisasi Data Covid – 19 Di Indonesia Menggunakan Tableau Big Data
Pages: 57-63
Copyright (c) 2023 Prayoga Pangestu, Dedy Hartama, Dedi Suhendro, Abdi Rahim Damanik, Selli Oktaviani
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
