Penerapan Dashboard Business Inteligence untuk Bongkar Muat Kapal pada Pelabuhan XYZ Menggunakan Metabase

Arbi Muh’adhim; Prayoga Dwi Supriyadi; Sanjaya Ramadhan; Ma’had Wicaksono

doi:10.61132/merkurius.v3i4.868

Authors

Arbi Muh’adhim Universitas Muhammadiyah Gresik
Prayoga Dwi Supriyadi Universitas Muhammadiyah Gresik
Sanjaya Ramadhan Universitas Muhammadiyah Gresik
Ma’had Wicaksono Universitas Muhammadiyah Gresik

DOI:

https://doi.org/10.61132/merkurius.v3i4.868

Keywords:

Business Intelligence, Dashboard, Port Operations, Resource Optimization

Abstract

The port is a vital infrastructure in the global logistics chain that connects sea and land transportation. The efficiency of cargo loading and unloading operations at the port is a critical factor influencing the smooth flow of goods and overall logistics costs. In this context, the use of Business Intelligence (BI) as an integrated technological system to support data collection, analysis, and presentation is becoming increasingly important for optimizing data-driven decision-making in port environments. XYZ Port, as one of the strategic ports in Indonesia, faces challenges in managing complex loading and unloading operations with increasing cargo volumes. The implementation of a BI dashboard offers a solution to visualize operational data in real-time, identify bottlenecks, and optimize resource allocation. This study aims to implement a BI dashboard for cargo handling operations at XYZ Port. The specific objectives include identifying information needs in cargo handling operations and developing a BI dashboard that suits the characteristics of port operations. The findings indicate that the dashboard effectively supports real-time decision-making and enhances operational efficiency. The study also highlights the importance of addressing technological infrastructure, human resource readiness, and system integration challenges in BI implementation.

References

Carlan, V., Naudts, D., Audenaert, P., Lannoo, B., & Vanelslander, T. (2019). Toward implementing a fully automated truck guidance system at a seaport: Identifying the roles, costs and benefits of logistics stakeholders. Journal of Shipping and Trade, 4(1). https://doi.org/10.1186/s41072-019-0054-5

Duan, L., & Xu, L. D. (2012). Business intelligence for enterprise systems: A survey. IEEE Transactions on Industrial Informatics, 8(3), 679–687. https://doi.org/10.1109/tii.2012.2188804

Gonçalves, C. T., Gonçalves, M. J. A., & Campante, M. I. (2023). Developing integrated performance dashboards visualisations using Power BI as a platform. Information, 14(11), 614. https://doi.org/10.3390/info14110614

Heilig, L., & Voß, S. (2017). Port-Centric information management in smart ports. In Ports and Networks (pp. 236–250). Routledge. https://doi.org/10.4324/9781315601540-15

Hermanto, E. A., Gemintang, S. A., Ariansyah, R., & Giovanny, M. A. (2023). ANALISIS PERBANDINGAN PENERAPAN BUSINESS INTELLIGENCE DI INDONESIA MENGGUNAKAN METODE SYSTEMATIC LITERATURE REVIEW. Djtechno: Jurnal Teknologi Informasi, 4(2), 344–354. https://doi.org/10.46576/djtechno.v4i2.3412

Maulidati, Z., Pangestu, S. B., & Aini, S. N. (2025). Ad-Hoc business intelligence for agile decision-making: A case study using adventure works 2022. INTEGER: Journal of Information Technology, 10(1). https://doi.org/10.31284/j.integer.2024.v10i1.7537

Metabase. (2014). Open source business intelligence, dashboards, and data visualizations. Metabase | Business Intelligence, Dashboards, and Data Visualization. https://www.metabase.com/

Murnawan, Samihardjo, R., & Nugraha, U. (2020). Design of the business intelligence dashboard for sales decision making. International Journal of Psychosocial Rehabilitation, 24(02), 3498–3513. https://doi.org/10.37200/ijpr/v24i2/pr200670

Mz, Y., Bororing, J. E., Rahayu, S., & Ramadhani, T. A. (2022). Aplikasi Dashboard Visualisasi Data Calon Mahasiswa Baru mengunakan Metabase. Edumatic: Jurnal Pendidikan Informatika, 6(1), 116–125. https://doi.org/10.29408/edumatic.v6i1.5483

Olubunmi Awodiji, T. (2021). Interactive dashboard design for manager, data analyst and data scientist perspective. NLP Techniques and Applications, 175–185. https://doi.org/10.5121/csit.2021.111914

Prahendratno, A., Mahendra, G. S., Zebua, R. S. Y., Tahir, R., Sepriano, S., Handika, I. P. S., Rahayu, P. W., Sudipa, I. G. I., & Efitra, E. (2023). BUSINESS INTELEGENT : Pengantar Business Intelligence dalam Bisnis. PT. Sonpedia Publishing Indonesia.

Ritonga, R. A., Ahmadi, N., Kusumastanto, T., Suwandi, R., Suwito, S. R., Hasriningtyas, S., Arafat, H., & Soleh, A. (2022). KESIAPAN IMPLEMENTASI SMART PORT DI INDONESIA. Coastal and Ocean Journal (COJ), 6(1), 8–23. https://doi.org/10.29244/coj.6.1.8-23

Saragih, E. H., Bayupati, I. P. A., & Putri, G. A. A. (2021). Pengembangan Business Intelligence Dashboard untuk Monitoring Aktivitas Pariwisata (Studi Kasus: Dinas Pariwisata Provinsi Bali). Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(6), 1159–1168. https://doi.org/10.25126/jtiik.2021863755

Siti hidayatul Khoirun Nisa’, & Rusdianto, R. Y. (2024). Pemanfaatan Visualisasi Data dalam Meningkatkan Pengambilan Keputusan Bisnis. Jurnal Informasi, Sains Dan Teknologi, 7(2), 200–208. https://doi.org/10.55606/isaintek.v7i2.290

Wibowo, A. S., & Andri, A. (2021). Dashboard business intelligence vusialisasi data akreditasi sekolah pada SMP Negeri 1 sembawa. Jurnal Nasional Ilmu Komputer, 2(4), 249–256. https://doi.org/10.47747/jurnalnik.v2i4.536