Data Analysis using Business Intelligence and Tableau for Visualizing Indonesia's Poverty Line

Fabianus Kevin Senduk, Retno Waluyo, Khairunnisak Nur Isnaini

Abstract


Poverty is the condition of being unable to meet an adequate standard of living. The poverty line serves as a key indicator for measuring poverty, particularly in developing countries. In Indonesia, poverty line data provided by the Central Statistics Agency (Badan Pusat Statistik – BPS) is typically presented in static tables, lacking in-depth analysis or annual trend insights needed to understand poverty dynamics across 578 regions. This study aims to analyze poverty line data in Indonesia using a Business Intelligence (BI) approach and visualize it through Tableau Public. BI was chosen for its capability to process complex data into more accessible and actionable information for decision-making. The output of this study is an interactive visualization dashboard that illustrates the distribution patterns and trends of the poverty line in Indonesia over the period 2022–2024. The dashboard offers in-depth insights into regional poverty shifts, including the identification of high-poverty areas and analysis of poverty line growth rates. It also serves as a strategic data-driven decision support tool. This research can be further developed by exploring the underlying factors driving poverty line fluctuations, applying the method to other dimensions such as income inequality, and leveraging alternative data visualization tools for a more comprehensive analysis.

Keywords


Business Intelligence; Visualisasi Data; Analisis Data; Tableau

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A. Adji, T. Hidayat, H. Tuhiman, S. Kurniawati, and A. Maulana, Pengukuran Garis Kemiskinan di Indonesia: Tinjauan Teoretis dan Usulan Perbaikan, vol. 48. 2020. Accessed: Dec. 23, 2024. [Online]. Available: https://www.tnp2k.go.id/download/79169WP480304FINAL.pdf

Badan Pusat Statistik (BPS), “Garis Kemiskinan Menurut Kabupaten/Kota (Rupiah/kapita/bulan), 2022-2024.” Accessed: Nov. 27, 2024. [Online]. Available: https://www.bps.go.id/id/statistics-table/2/NjI0IzI=/garis-kemiskinan-menurut-kabupaten-kota.html

R. Nuraini, “Decision Support System for Hydroponic Vegetable Seed Selection using Exponential Comparison Method,” Jurnal Pilar Nusa Mandiri, vol. 18, no. 2, p. 124, Sep. 2022, doi: 10.33480/pilar.v18i2.3471.

R. I. Borman, D. A. Megawaty, and A. Attohiroh, “Implementasi Metode TOPSIS pada Sistem Pendukung Keputusan Pemilihan Biji Kopi Robusta yang Bernilai Mutu Ekspor (Studi Kasus : PT. Indo Cafco Fajar Bulan Lampung),” Fountain of Informatics Journal, vol. 5, no. 1, p. 15, Mar. 2020, doi: 10.21111/fij.v5i1.3828.

L. D. Rachmawati and F. N. Hasan, “Jurnal Informatika dan Rekayasa Perangkat Lunak Implementasi Business Intelligence untuk Analisa dan Visualisasi Data Penyebab Kematian di Indonesia menggunakan Platform Tableau,” Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 5, Mar. 2023, [Online]. Available: www.kaggle.com

T. Tumini and E. S. Subekti, “Implementasi Business Intelligence untuk menganalisis Data Proses Manufaktur menggunakan Google Data Studio,” Jurnal Ilmiah Teknik Informatika dan Komunikasi, vol. 3, no. 3, pp. 143–151, Sep. 2023, doi: 10.55606/juitik.v3i3.625.

E. Marvaro and R. S. Samosir, “Penerapan Business Intelligence dan Visualisasi Informasi di CV. Mitra Makmur dengan menggunakan Dashboard Tableau,” Kalbiscentia, Jurnal Sains dan Teknologi, Aug. 2021, Accessed: Jan. 01, 2025. [Online]. Available: http://ojs.kalbis.ac.id/index.php/kalbiscientia/article/view/197

D. Triyanto, M. Sholeh, and F. N. Hasan, “KLIK: Kajian Ilmiah Informatika dan Komputer Implementasi Business Intelligence menggunakan Tableau untuk Visualisasi Data Dampak Bencana Banjir di Indonesia,” Media Online), vol. 3, no. 6, pp. 586–594, 2023, doi: 10.30865/klik.v3i6.769.

P. Klein et al., “Visual Attention While Solving the Test of Understanding Graphs in Kinematics: An Eye-Tracking Analysis,” Eur J Phys, vol. 41, no. 2, 2020, doi: 10.1088/1361-6404/ab5f51.

H. Wiyono, Dasar - Dasar Visualisasi Data. Balai Pengembangan Kompetensi PUPR Wilayah III Jakarta, 2023.

F. Skender and V. Manevska, “Data Visualization Tools-Preview and Comparison,” APA, 2022.

D. Saepuloh, “Visualisasi Data Covid 19 Provinsi DKI menggunakan Tableau,” Jurnal Riset Jakarta, vol. 13, no. 2, Dec. 2020, doi: 10.37439/jurnaldrd.v13i2.37.

M. N. Razali, S. A. Manaf, R. B. Hanapi, M. R. Salji, L. W. Chiat, and K. Nisar, “Enhancing Minority Sentiment Classification in Gastronomy Tourism: A Hybrid Sentiment Analysis Framework with Data Augmentation, Feature Engineering and Business Intelligence,” IEEE Access, vol. 12, p. 49393, 2024, doi: 10.1109/ACCESS.2024.3362730.

F. A. Sariasih, “Implementasi Business Intelligence Dashboard dengan Tableau Public untuk Visualisasi Propinsi Rawan Banjir di Indonesia,” Jurnal Pendidikan Tambusai, vol. 6, pp. 14424–14431, 2022, Accessed: Feb. 23, 2025. [Online]. Available: https://jptam.org/index.php/jptam/article/view/4715

S. N. Zahra and P. E. P. Utomo, “Visualisasi Data Penjualan Barang Retail di Seluruh Dunia menggunakan Tableau,” Jurnal Nasional Ilmu Komputer, vol. 4, no. 3, pp. 2746–1343, 2023, doi: 10.47747/jurnalnik.v4i3.1217.

R. Wati, A. Fauzi, I. Nawawi, H. Rachmi, and S. Nur Azizah, “Jurnal Aruna Mengabdi (ARMI): Pelatihan Google Spreadsheet untuk mempermudah Pekerjaan bagi PKK Kelurahan Paledang,” vol. 1, no. 1, p. 18, 2023, [Online]. Available: https://ejournal.lotusaruna.id/index.php/armi

A. Fitria and L. Z. Yadi, “Pemanfaatan Business Intelligence untuk Visualisasi Data dan Pemetaan Kasus Gizi Buruk dan Gizi Kurang menggunakan TableAu (Studi Kasus Dinas Kesehatan Kota Prabumulih),” Institute of Computer Science (IOCS), pp. 3436–3445, 2022.

E. H. Saragih, I. P. A. Bayupati, and G. A. A. Putri, “Pengembangan Business Intelligence Dashboard untuk Monitoring Aktivitas Pariwisata (Studi Kasus: Dinas Pariwisata Provinsi Bali),” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 8, p. 1161, 2021, doi: 10.25126/jtiik.202183755.

A. Suhendar and T. Hikmatunnisa, “Penerapan Business Intelligence pada Peluang Jenis Usaha Baru Usaha Mikro, Kecil, dan Menengah dengan menggunakan Teknologi Online Analytical Processing,” JSiI (Jurnal Sistem Informasi), vol. 9, no. 2, pp. 115–118, Sep. 2022, doi: 10.30656/jsii.v9i2.5183.

N. K. Zuhal, “Study Comparison K-Means Clustering dengan Algoritma Hierarchical Clustering,” 2022.

J. W. Creswell and J. D. Creswell, Research Design Qualitative, Quantitative, and Mixed Methods Approaches, Fifth edition. SAGE Publications, Inc., 2018. Accessed: Dec. 23, 2024. [Online]. Available: https://spada.uns.ac.id/pluginfile.php/510378/mod_resource/content/1/creswell.pdf

U. Sulung and M. Muspawi, “Memahami Sumber Data Penelitian: Primer, Sekunder, dan Tersier,” Jurnal Edu Research, vol. 5, Sep. 2024, Accessed: Feb. 23, 2025. [Online]. Available: https://iicls.org/index.php/jer/article/view/238

N. P. A. W. Widiari, I. M. A. D. Suarjaya, and D. P. Githa, “Teknik Data Cleaning menggunakan Snowflake untuk Studi Kasus Objek Pariwisata di Bali,” JURNAL ILMIAH MERPATI, vol. 8, pp. 137–145, Aug. 2020, doi: 10.24843/JIM.2020.v08.i02.p07.

J. Lullail, Y. Aini, A. Setiawan, and L. Fimawahib, “Visualisasi Data Honda menggunakan Platform Data Studio,” Riau Journal of Computer Science, vol. 10, no. 1, p. 68, 2024, doi: 10.30606/rjocs.v10i1.2579.

E. Novalia Pusparini, “Literature Review: Data Management, Data Analytics, and Business Intelligence for Organization,” Jurnal Ilmu Komputer Dan Teknologi Informasi, vol. 2, no. 4, 2024, doi: 10.61132/neptunus.v2i4.429.

A. Riviani, L. A. Rahmawati, and C. B. Santoso, “Perancangan Data Warehouse dan Implementasi Tableau untuk Analisis Data di Sektor Pariwisata,” Prosiding Seminar Nasional LPPM UMJ, Sep. 2024, [Online]. Available: http://jurnal.umj.ac.id/index.php/semnaskat

K. Pebriawan et al., “Visualisasi Data Sebaran Wilayah Pariwisata di Provinsi Bali dengan Platform Tableau,” 2023. [Online]. Available: https://ejurnal.umri.ac.id/index.php/SEIS/index

Y. Padang, Abdunnur, and M. R. Syahrir, “Analisis Kuartil, Desil, dan Persentil pada Ukuran Panjang Udang Bintik Coklat (Metapenaeus Demani) di Perairan Muara Ilu, Kabupaten Kutai Kartanegara (Analysis of Quartile, Decile, and Percentile on Length of Brown Spot Shrimp (Metapenaeus Demani) in Ilu Estuary Waters, Kutai Kartanegara Regency),” Tropical Aquatic Sciences, vol. 2, no. 1, p. 44, 2023, doi: 10.30872/tas.v2i1.

F. K. Senduk, “Analisis Garis Kemiskinan Indonesia (2022-2024).” Accessed: Dec. 23, 2024. [Online]. Available: https://public.tableau.com/app/profile/fabianus.senduk/viz/AnalisisGarisKemiskinanIndonesia2022-2024/maindashboard

“Memahami dasar-dasar privasi di Google Dokumen, Spreadsheet, Slide & Vids.” Accessed: Feb. 28, 2025. [Online]. Available: https://support.google.com/docs/answer/10381817?hl=id&dark=1&sjid=10288864305101420484-NC

“Tableau Platform Security.” Accessed: Mar. 01, 2025. [Online]. Available: https://www.tableau.com/enterprise-it/security

“Tableau Commitment to Privacy Protection.” Accessed: Mar. 01, 2025. [Online]. Available: https://www.tableau.com/do-not-sell-my-personal-information#:~:text=Learn%20about%20our%20commitment%20to,how%20Tableau%20handles%20personal%20information.




DOI: https://doi.org/10.32520/stmsi.v14i3.4993

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