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p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal International Journal of Management Science and Information Technology (IJMSIT)
Syaban Maulana
Politeknik Takumi
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Tableau-Based Business Intelligence Analysis For the 4P Strategy and Product Sales KPIs in Vending Machines at Minori Group Lambok Rommy Sulaeman; Chowal Jundy Kumoro; Syaban Maulana; Davina Clarissa Rabbani
International Journal of Management Science and Information Technology Vol. 5 No. 2 (2025): July - December 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v5i2.5979

Abstract

This study aims to analyze the application of Business Intelligence (BI) using Tableau in supporting data-driven decision making in the marketing mix strategy (4Ps) and Key Performance Indicators (KPIs) for vending machine product sales at Minori Group. With the increasing need for efficiency and competition in the South Cikarang industrial area, Minori Group faces challenges in integrating marketing and sales data scattered across various sources. The research method used is a descriptive quantitative approach with the following stages: data collection from vending machine applications, data cleaning using Excel, integration into Tableau for visual analysis, interpretation of visualization results, and preparation of strategic recommendations. The results show that visualization with Tableau is able to provide a comprehensive picture of product performance based on the aspects of Product, Price, Place, and Promotion. The main findings show that inconsistent product placement per slot (BIN) causes sales analysis to be less accurate, while KPI calculations reveal significant variations in performance between products. Tableau has proven to be effective in helping management identify sales patterns, high-performing products, and areas that need to be optimized through promotional strategies and slot rearrangement. The integration of Marketing Mix theory, Business Intelligence, and Technology Acceptance Model (TAM) confirms that Tableau not only serves as a visualization tool, but also as a strategic platform in building a data-driven organizational culture. The implementation of BI through Tableau is expected to increase marketing effectiveness, operational efficiency, and company profitability.
Development of Intelligent Decision Support System Based on Quadrant Analysis, Time Series Trend Analysis, and Automatic Planogram Generation for Vending Machine Product Optimization Rizaldi Putra; Syaban Maulana; Tessalonika Audry Polnaya; Muhammad Zaky Fahriansyah
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8277

Abstract

Product management in a vending machine business requires fast and data-driven decision-making to increase sales effectiveness and profitability. However, decision-making related to price adjustments, product bundling, product replacements, and product arrangement on vending racks is still mostly done manually based on the manager's experience, so it has the potential to produce less than optimal decisions. This research aims to develop an Intelligent Decision Support System that is able to produce business strategy recommendations through the integration of Quadrant Analysis, Time Series Trend Analysis, and Automatic Planogram Generation. The research data was obtained from the results of exporting the vending machine transaction database imported into the application in CSV or Excel format, so that the system does not depend on direct integration with the Application Programming Interface (API). Quadrant Analysis is used to group products based on sales performance and profit contribution, while Time Series Trend Analysis is used to evaluate historical sales trends as a support for decision validation, rather than as a sales prediction method. The results of the second analysis were processed using a rule-based decision engine mechanism to produce recommendations in the form of price adjustments, product bundling, maintaining or replacing products, and compiling an automatic planogram based on product performance priorities. The resulting planogram can still be adjusted manually by the user so that it still provides flexibility in operational decision-making. In addition, the system presents profit analysis based on product, machine, and location as the basis for business evaluation. The resulting artifacts are in the form of a decision support system application that not only presents data visualization, but also automatically generates strategic recommendations to help managers improve the effectiveness of product management in the vending machine business.
Co-Authors Chowal Jundy Kumoro Davina Clarissa Rabbani Lambok Rommy Sulaeman Muhammad Zaky Fahriansyah Rizaldi Putra Tessalonika Audry Polnaya