Published: 2025-04-01
Sales Data Visualization for Rumah Berkebun Shopee Store Using Business Intelligence and Google Data Studio
DOI: 10.35870/ijsecs.v5i1.3663
Dito Ramadhani, Muhammad Adie Syaputra
- Dito Ramadhani: Universitas Dharma Wacana , Indonesia
- Muhammad Adie Syaputra: Universitas Dharma Wacana , Indonesia
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Abstract
This study focuses on the analysis and visualization of sales data from Rumah Berkebun through a Business Intelligence (BI) approach, facilitated by the Google Data Studio platform. Utilizing an interactive dashboard, the research uncovers sales trends for key products such as durian and avocado seeds while identifying prominent seasonal demand variations. The dataset spans a two-year period (2022-2023) and incorporates critical metrics, including total sales, transaction volume, and order cancellation rates. Findings indicate notable seasonal fluctuations, with peak sales recorded in June 2022 and December 2023, alongside dominant market contributions from South Sumatra and Lampung. Conversely, regions like Bali and Nusa Tenggara exhibited substantial declines in sales performance. Quantitative insights were derived using statistical methods such as linear trend analysis and geographic heatmaps to map sales patterns and regional disparities. A significant challenge lies in the elevated order cancellation rates, largely attributed to payment-related obstacles, which hinder customer satisfaction. The adoption of BI has demonstrated its value in optimizing operational efficiency, enabling targeted stock and promotional strategies, and bolstering Rumah Berkebun competitive edge in digital and e-commerce landscapes. These results underscore the critical role of BI technology in fostering data-driven decision-making for online businesses.
Keywords
Business Intelligence ; Sales Performance ; Interactive Dashboard ; Data Visualization
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This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 1 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i1.3663
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Dito Ramadhani
Informatics Engineering Study Program, Faculty of Business Technology and Science, Universitas Dharma Wacana, Metro City, Lampung Province, Indonesia
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Aryanti, D., & Setiawan, J. (2018). Visualisasi data penjualan dan produksi PT Nitto Alam Indonesia periode 2014-2018. Ultima InfoSys: Jurnal Ilmu Sistem Informasi, 9(2), 86-91. https://doi.org/10.31937/si.v9i2.991
-
Apridonal, Y., Mardalius, M., & Dristyan, F. (2023). Optimalisasi e-commerce sebagai strategi bisnis digital. Journal of Indonesian Social Society (JISS), 1(2), 86-91. https://doi.org/10.59435/jiss.v1i2.139
-
Zahra, S. N., & Utomo, P. E. P. (2023). Visualisasi data penjualan barang retail di seluruh dunia menggunakan Tableau. Jurnal Nasional Ilmu Komputer, 4(3), 12-21. https://doi.org/10.47747/jurnalnik.v4i3.1217
-
Pendawa, P. D. (2023). Visualisasi data penjualan pada online shop Shillo Store dengan teknik business intelligence. KALBISIANA Jurnal Sains, Bisnis dan Teknologi, 9(3), 548-559. https://doi.org/10.53008/kalbisiana.v9i3.1093
-
Arfandi, Z., Yanto, B., Sabri, K., Aini, Y., & Lubis, A. (2024). Analisa visualisasi data penjualan dan tingkat kepuasan penjualan menggunakan platform Lookerstudio. RJOCS (Riau Journal of Computer Science), 10(1), 38-45. https://doi.org/10.30606/rjocs.v10i1.2402
-
Zai, F. I., Mustafa, S. R., Aini, Y., Setiawan, A., & Sena, M. D. (2024). Visualisasi BigQuery data penjualan toko sembako menggunakan platform Loker Studio. RJOCS (Riau Journal of Computer Science), 10(1), 46-52. https://doi.org/10.30606/rjocs.v10i1.2403
-
-
Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54(8), 88-98. https://doi.org/10.1145/1978542.1978562
-
Bhutani, M. (2019). Enhancing user experience while retrieving information via dashboard [Master’s thesis, KTH Royal Institute of Technology]. Digitala Vetenskapliga Arkivet. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262728
-
-
-
Mahebu, M. A., & Samosir, R. S. (2023). Visualisasi data penjualan CV. Waskat Karya Metal menggunakan pendekatan business intelligence. KALBISCIENTIA Jurnal Sains dan Teknologi, 10(2), 138-147. https://doi.org/10.53008/kalbiscientia.v10i2.2143
-
-
Manurung, N. (2024). Implementasi Google Data Studio pada visualisasi data bola bass ball dalam bentuk dashboard. RJOCS (Riau Journal of Computer Science), 10(1), 76-81. https://doi.org/10.30606/rjocs.v10i1.2404
-
Fauziah, F. (2020). Strategi komunikasi bisnis online shop “Shopee” dalam meningkatkan penjualan. Abiwara: Jurnal Vokasi Administrasi Bisnis, 1(2), 45-53. https://doi.org/10.31334/abiwara.v1i2.792
-
Ramadhani, Y., Khairina, D. M., & Maharani, S. (2024). Implementasi business intelligence dalam analisa penjualan mobil Mitsubishi menggunakan visualisasi data. Adopsi Teknologi dan Sistem Informasi (ATASI), 3(1), 1-11. https://doi.org/10.30872/atasi.v3i1.435
-
Lullail, J., Setiawan, A., Fimawahib, L., & Aini, Y. (2024). Implementasi business intelligence untuk analisa dan visualisasi data Honda menggunakan platform Data Studio. RJOCS (Riau Journal of Computer Science), 10(1), 68-75. https://doi.org/10.30606/rjocs.v10i1.2579
-
Minatania, A. (2023). Visualisasi data Covid-19 tahun 2021 di Jawa Barat menggunakan Google Data Studio. Jurnal Informasi dan Komputer, 11(1), 44-51. https://doi.org/10.35959/jik.v11i01.347
-
-
Hendrawan, S. A., & Setyantoro, D. (2022). Pemanfaatan dashboard business intelligence untuk laporan penjualan pada Superstore. Jurnal Ilmiah Teknik Informatika (TEKINFO), 23(1), 46-52. https://doi.org/10.37817/tekinfo.v23i1.1876.

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