Perancangan Business Intelligence PT. Niagamas Lestari Gemilang untuk Meningkatkan Penjualan
DOI:
https://doi.org/10.29313/bcsies.v6i1.21705Keywords:
Business Intelligence, STP, Marketing MixAbstract
Abstract. PT. Niagamas Lestari Gemilang, a construction equipment and machinery distributor company, faces challenges in formulating an effective sales strategy due to its reliance on conventional monthly reports. Limited information causes decision-making to be subjective and not supported by data analysis, resulting in sales fluctuations and failure to achieve targets. This research designs and implements a Business Intelligence (BI) system using the Business Intelligence Roadmap method which consists of six stages: justification, planning, business analysis, design, construction, and deployment. The integration of Segmentation, Targeting, Positioning (STP) and Marketing Mix analysis frameworks is applied to process sales data. Data analysis involves clustering customers using the K-Means algorithm and developing interactive dashboards with Microsoft Power BI. The result of the research is a prototype of a Business Intelligence system in the form of an analytical dashboard that presents sales information in a multidimensional manner. The segmentation analysis maps the market into two clusters: Region 1 (Bandung) as the primary market with a contribution of 64.8% and Region 2 (Outside Bandung) as the secondary market. The product analysis identified Daiden and Izumi brand welding machines and wind compressors as superior products. The BI dashboard allows analysis of the pricing effectiveness, regional performance, and capabilities of the marketing team. In conclusion, BI design has been proven to support data-driven decision-making, transform transactional data into actionable insights, and enable companies to formulate more objective and measurable sales strategies.
Abstrak. PT. Niagamas Lestari Gemilang, perusahaan distributor peralatan konstruksi dan mesin, menghadapi tantangan dalam merumuskan strategi penjualan yang efektif karena ketergantungan pada laporan bulanan konvensional. Keterbatasan informasi menyebabkan pengambilan keputusan bersifat subjektif dan tidak didukung analisis data sehingga berakibat pada fluktuasi penjualan dan kegagalan mencapai target. Penelitian ini merancang dan mengimplementasikan sistem Business Intelligence (BI) menggunakan metode Business Intelligence Roadmap yang terdiri dari enam tahapan: justification, planning, business analysis, design, construction, dan deployment. Integrasi kerangka analisis Segmentation, Targeting, Positioning (STP) dan Bauran Pemasaran diterapkan untuk mengolah data penjualan. Analisis data melibatkan klasterisasi pelanggan menggunakan algoritma K-Means dan pengembangan dashboard interaktif dengan Microsoft Power BI. Hasil penelitian adalah prototipe sistem Business Intelligence berupa dashboard analitis yang menyajikan informasi penjualan secara multidimensional. Analisis segmentasi memetakan pasar menjadi dua klaster: Wilayah 1 (Bandung) sebagai pasar primer dengan kontribusi 64,8% dan Wilayah 2 (Luar Bandung) sebagai pasar sekunder. Analisis produk mengidentifikasi mesin las dan kompresor angin merek Daiden dan Izumi sebagai produk unggulan. Dashboard BI memungkinkan analisis efektivitas harga, kinerja wilayah, dan kapabilitas tim pemasaran. Kesimpulannya, perancangan BI terbukti mendukung pengambilan keputusan berbasis data, mentransformasi data transaksional menjadi actionable insight, dan memungkinkan perusahaan merumuskan strategi penjualan yang lebih objektif dan terukur.
References
Alif Aulia Rahmansyah, Djamaludin. Perancangan Business Intelligence untuk Menganalisa Strategi Pemasaran PT. XYZ. Jurnal Riset Teknik Industri. 2023 Dec 19;147–56. doi:10.29313/jrti.v3i2.2896
Sodikin VAZ, Reni Amaranti, Djamaludin. Perancangan Sistem Informasi Manajemen Gudang PT. X. Jurnal Riset Teknik Industri. 2021 Oct 25;1(1):58–67. doi:10.29313/jrti.v1i1.141
Firmansyah RD. Perancangan Sistem Informasi Manajemen Persediaan UD. X. Jurnal Riset Teknik Industri. 2022 Jul 8;47–56. doi:10.29313/jrti.v2i1.940
Ahmad, A. (2015). Business Intelligence for Sustainable Competitive Advantage (hlm. 3–220). https://doi.org/10.1108/S1069-096420150000022014
Akbar, R., Silvana, M., Hersyah, M. H., & Jannah, M. (2020). Implementation of Business Intelligence for Sales Data Management Using Interactive Dashboard Visualization in XYZ Stores. 2020 International Conference on Information Technology Systems and Innovation (ICITSI), 242–249. https://doi.org/10.1109/ICITSI50517.2020.9264984
Grossmann, W., & Rinderle-Ma, S. (2015). Fundamentals of Business Intelligence. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-46531-8
Kotler, P., & Amstrong, G. (2018). Principles of Marketing Global Edition (15 ed.). Pearson Education.
Kotler, P., & Keller, K. L. (2016). Marketing Management (15 ed.). Pearson Education.
Mahebu, M. A., & Samosir, R. S. (2023). A Visualisasi Data Penjualan CV. Waskat Karya Metal Menggunakan Pendekatan Business intelligence. KALBISCIENTIA Jurnal Sains dan Teknologi, 10(02), 138–147. https://doi.org/10.53008/kalbiscientia.v10i2.2143
Moss, L. T., & Atre, S. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for DecisionSupport Applications. Addison Wesley.
Sugiyono. (2016). Metode Penelitian, Kuantitatif, Kualitatif, dan R&D. Alfabeta.
Utami, C. B., Faruk, L., & Musyarrofah, O. (2015). PENGARUH BUSINESS INTELLIGENCE TERHADAP DUNIA BISNIS. ICIT Journal, 1(1), 16–25. https://doi.org/10.33050/icit.v1i1.6
WIJAYA, C., & Purnamasari, S. D. (2020). Dashboard Business Intelligence Untuk Mendukung Strategi Pemasaran Vitamin Karet Dan Sawit. Bina Darma Conference on Computer Science (BDCCS), 2(4), 393–399.
