Data Visualization Of House Of Worship Distribution In The IKN Nusantara Region Using Python

  • I Kadek Noppi Adi Jaya UNHI
  • Fauzi Fauzi Information Systems Study Program, Bakti Nusantara Institute, Pringsewu, Lampung
  • Agus Suryana Information Systems Study Program, Bakti Nusantara Institute, Pringsewu, Lampung
  • Albertus Dwiyoga Widiantoro Information Systems Study Program, UNIKA Soegijapranata, Semarang
  • I Dewa Kadek Laksana Digita Information Systems Study Program, Faculty of Information Technology and Science, Hindu Univesity of Indonesia, Denpasar
DOI: https://doi.org/10.24843/JIM.2023.v11.i01.p01

Abstract

Nusantara, Indonesia's new capital, has a land area 256,142 ha and a marine area 68,189 ha. Transmigrant residents in the North Penajam Paser Regency region has increased as a result. The difficulty of finding a place of worship in the closest location because they are unfamiliar with their location or the nearby roadways. We can utilize data visualization to show the distribution of places of worship in order to solve this issue. Analysis was done on several types of houses of worship, including mosques, churches, and musholla. Python is the programming language, and the libraries used are NumPy, Pandas, Matplotlib, Seaborn, RegEx, and Folium. Muslims for the majority of places of worship in IKN Nusantara (91.26%), musholla making up 57.92% of the total and mosques making up 33.33% and 8.74% are owned by Christians. Sukaraja Village, Semoi Dua Village, Argo Mulyo Village, and Tengin Baru Village have the highest concentration. Keywords: Data Visualization, House of Worship, IKN Nusantara, Python

Published
2023-04-26
How to Cite
ADI JAYA, I Kadek Noppi et al. Data Visualization Of House Of Worship Distribution In The IKN Nusantara Region Using Python. Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi), [S.l.], v. 11, n. 1, p. 1-12, apr. 2023. ISSN 2685-2411. Available at: <https://ojs.unud.ac.id/index.php/merpati/article/view/98039>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/JIM.2023.v11.i01.p01.
Citation Formats
Issue
Vol 11 No 1 (2023): Vol. 11, No. 1, April 2023
Section
Articles

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