Basic Application of Business Intelligence in making E-Commerce Buyer Dashboard Indonesian Using Tableau Tools Development

Uya Asy Syuura Anandri; Abdullah

doi:10.52435/complete.v6i2.747

Authors

Uya Asy Syuura Anandri Information System, Faculty of Engineering and Computer Science, Islamic University of Indragiri, Indonesia https://orcid.org/0009-0000-2385-7400
Abdullah Information System, Faculty of Engineering and Computer Science, Islamic University of Indragiri, Indonesia https://orcid.org/0000-0001-5169-7678

DOI:

https://doi.org/10.52435/complete.v6i2.747

Keywords:

Business Intelligence, Tableau, OpenRefine, E-Commerce, Dashboard, Data Science

Abstract

This research examines the implementation of Business Intelligence (BI) for the creation of an Indonesian e-commerce buyer dashboard in 2024 with the aim of increasing the visibility of operational KPI and demonstrating a reproducible pipeline from data cleaning to visualization. The main issues addressed are the quality of order-level data (provincial writing variants, date format, numerical values, and PII anonymization) as well as the need to calculate buyer metrics (unique buyers, repeat rate) which is rarely ava1ilable in public aggregate data. The methods used include: (1) data cleaning and harmonizing using OpenRefine; (2) numerical transformation and validation with Python (pandas); (3) creating interactive worksheets and dashboards in Tableau (sales map per province; monthly trend line; bar with avg sales per product; sales pie by gender); and (4) sensitivity analysis to assess the impact of cleaning step variation on buyer-level KPI. Using the order-level dataset of cleaning results (1,000 transactions), a total revenue of Rp 2,298,975,000, 1,000 orders, and 178 unique buyers were found; seasonal patterns were seen with a peak in the fourth quarter and revenue concentration in urban areas (DKI Jakarta, West Java). The top-10 products contribute a significant portion of revenue, and repeat buyers show an important role in the sales structure

Author Biographies

Uya Asy Syuura Anandri, Information System, Faculty of Engineering and Computer Science, Islamic University of Indragiri, Indonesia

Uya Asy Syuura Anandri is an undergraduate (S1) student in the Information Systems Program at Universitas Islam Indragiri (UNISI) and is registered with ORCID iD 0009-0000-2385-7400. He specializes in information systems and database engineering, with particular expertise in Entity–Relationship Diagram (ERD) design and descriptive statistical analysis of academic datasets. He also conducts applied research on business models for micro, small, and medium enterprises (UMKM), including community-engaged studies on innovative UMKM initiatives in the Tembilahan area. His contributions include several articles and conference papers on ERD development, information-systems auditing, applied data analysis, and UMKM empowerment projects within the local academic context.

Abdullah, Information System, Faculty of Engineering and Computer Science, Islamic University of Indragiri, Indonesia

Prof. Dr. H. Abdullah, S.Si., M.Kom., Ph.D. is a Professor in the Department of Information Systems, Faculty of Engineering and Computer Science at Universitas Islam Indragiri (UNISI). His research focuses on information systems and the application of machine learning to practical problems, including work on convolutional neural network (CNN) and TensorFlow–based methods for food-safety detection. Prof. Abdullah is actively engaged in academic supervision, applied research projects, and knowledge dissemination through national conferences and institutional collaborations.

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