VISUALISASI DATA OPINI PUBLIK MENGGUNAKAN LOOKER STUDIO (STUDI KASUS PEMILIHAN UMUM PRESIDEN INDONESIA 2024)

Eko Prasetyo Wicaksono; Paniran

doi:10.33884/jif.v12i02.8918

Authors

Eko Prasetyo Wicaksono Universitas Mataram
Paniran Universitas Mataram

DOI:

https://doi.org/10.33884/jif.v12i02.8918

Keywords:

Visualisasi Data, Looker Studio, Dashboard, BigQuery

Abstract

In 2024, Indonesia held presidential and vice presidential elections. Before the election took place, researchers gathered sentiment data from X and news sources from January 1, 2023 to September 1, 2023. The data collected was not well-visualized, resulting in suboptimal information. For this study, researchers applied data visualization using Google Looker Studio, which enables data presentation in table and graphic formats, making it more engaging. Data will be stored in BigQuery, which is connected to Looker Studio. The results of the study showed that the validity of the data based on its source was 50.1% real and 49.9% fake. There were five top topics for each candidate, including Public Figure, Leader, Political Policy, Community, and Election. Based on the sentiment flow analysis, most data originated from news sources and the rest from X social media.

References

R. Dania and P. K. Nisa, “Peran Dan Pengaruh Media Sosial Dalam Kampanye Pemilihan Presiden 2024,” Virtu J. Kaji. Komunikasi, Budaya Dan Islam, vol. 3, no. 2, pp. 103–109, 2023, doi: 10.15408/virtu.vxxx.xxxxx.

I. K. Dharmendra et al., “Visualisasi Data Opini Publik pada Media Sosial Twitter ( Studi Kasus : Nusantara Sebagai IKN Indonesia ),” vol. 07, pp. 214–222, 2022.

S. Suhardi, W. Walim, H. Priyandaru, W. Prabowo, and H. Priatmojo, “The IMPLEMENTASI INFORMATION RETRIEVAL SYSTEM UNTUK KLASIFIKASI BERITA OFFLINE DI INDONESIA MENGGUNAKAN METODE EXTENDED BOOLEAN,” CERMIN J. Penelit., vol. 5, no. 1, p. 124, 2021, doi: 10.36841/cermin_unars.v5i1.951.

D. Mangal and D. K. Sharma, “A Framework for Detection and Validation of Fake News via Authorize Source Matching,” Lect. Notes Networks Syst., vol. 179 LNNS, pp. 577–586, 2021, doi: 10.1007/978-981-33-4687-1_54.

A. Hadi Wijaya, Ipriadi, and W. Fitri, “Dasboard dan Visualisasi Reservasi Buka Puasa di Hotel XYZ Menggunakan Looker Studio & Google Form,” J. Informatics Busisnes, vol. 01, no. 04, pp. 354–359, 2024.

Fernando and Purwanti, “Dashboard Visualisasi Bencana di Provinsi Jawa Barat Menggunakan Looker Studio Berbasis Web,” vol. 24, no. 2, pp. 65–72, 2023.

N. M. Farhan and B. Setiaji, “Indonesian Journal of Computer Science,” Indones. J. Comput. Sci., vol. 12, no. 2, pp. 284–301, 2023, [Online]. Available: http://ijcs.stmikindonesia.ac.id/ijcs/index.php/ijcs/article/view/3135

E. Irawanzaiferigmailcom, “VISUALISASI BIGQUERY DATA PENJUALAN TOKO SEMBAKO Analisis Visualisasi Bigquery Data Penjualan Toko Sembako Menggunakan Flatfrom Loker Studio,” vol. 10, no. 1, pp. 46–52, 2024.

D. F. and F. N. H. Muhammad Ardhi Ryan Saputra, “Penerapan Business Intelligence Untuk Menganalisis Data Kasus Covid-19 Di Provinsi Jawa Barat Menggunakan Platform Google Data Studio,” J. Ilm. Komputasi, vol. 22, no. 2, pp. 187–196, 2023, doi: 10.32409/jikstik.22.2.3362.

I. P. W. Prasetia and I. N. H. Kurniawan, “Implementasi ETL (Extract, Transform, Load) pada Data warehouse Penjualan Menggunakan Tools Pentaho,” TIERS Inf. Technol. J., vol. 2, no. 1, pp. 1–8, 2021, doi: 10.38043/tiers.v2i1.2844.

F. A. Sariasih, “Implementasi Business Intelligence Dashboard dengan Tableau Public untuk Visualisasi Propinsi Rawan Banjir di Indonesia,” J. Pendidik. Tambusai, vol. 6, pp. 14424–14431, 2022.

T. Aristi Saputri, S. Muharni, and A. Perdana, “Pemanfaatan Google Data Studio Untuk Visualisasi Data Bagi Kepala Gudang UD Salim Abadi,” Ilmu Komput. Untuk Masy., vol. 2, no. 2, pp. 67–72, 2021.

M. Ali and M. Menap, “Workshop Pengumpulan dan Visualisasi Data Online Survei Kepuasan Masyarakat terhadap Pelayanan Puskesmas di Lombok Tengah,” Abdimas J. Pengabdi. Masy. Univ. Merdeka Malang, vol. 6, no. 2, pp. 279–289, 2021, doi: 10.26905/abdimas.v6i2.5384.

Gallaecio, “scrapy,” 2024. https://github.com/scrapy/scrapy (accessed May 15, 2024).

Ranahaani, “GNews,” 2024. https://github.com/ranahaani/GNews (accessed May 15, 2024).

S. Kosikov, L. Ismailova, and V. Wolfengagen, “Data Enrichment in the Information Graphs Environment Based on a Specialized Architecture of Information Channels,” Procedia Comput. Sci., vol. 190, no. 2019, pp. 492–499, 2021, doi: 10.1016/j.procs.2021.07.001.