Design of a Sales Performance System for SMEs based on Business Intelligence and Data Warehouse
Abstract
The influence of information technology today is powerful. It impacts people's lives because technological changes are running so fast and affect the way of thinking and behaving in competition in the business world and organizations. Small and Medium Enterprises (SMEs) must be able to adapt to this technology to maintain their business. It means that digitizing SMEs means integrating technology into all business activities. In this study, Toko Cerme is the object of research. The Toko Cerme is a SMEs in the form of a minimarket located in Central Java, Indonesia. The Toko Cerme takes advantage of technology to help run business processes so that they can be managed optimally. In running its business, The Toko Cerme is currently using an information system to input product data and transaction activities. The purpose of this research is to propose a Design of a Sales Performance System based on Business Intelligence and a Data Warehouse to support business processes at the Toko Cerme so that it can efficiently process data and information in the future. From the research that the authors conducted, it can be concluded that the results of this study are the creation of a data warehouse and business intelligence design using the nine steps Kimbal method. At the same time, Pentaho Data Integration (PDI) is a tool. The design is used as a reference in producing information relating to sales transactions.
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References
S. Kraus, S. Durst, J. J. Ferreira, P. Veiga, N. Kailer, and A. Weinmann, “Digital transformation in business and management research: An overview of the current status quo,” Int. J. Inf. Manage., vol. 63, p. 102466, 2022.
C. Troise, V. Corvello, A. Ghobadian, and N. O’Regan, “How can SMEs successfully navigate VUCA environment: The role of agility in the digital transformation era,” Technol. Forecast. Soc. Change, vol. 174, p. 121227, 2022.
D. I. S. Saputra, K. Indartono, and S. W. Handani, “Business Models based Technology for Startup,” J. Innov. Bus. Econ., vol. 03, no. 02, pp. 91–98, 2019, doi: 10.22219/jibe.v3i02.10168.
P. M. Bican and A. Brem, “Digital Business Model, Digital Transformation, Digital Entrepreneurship: Is There A Sustainable ‘Digital’?,” Sustainability, vol. 12, no. 13, p. 5239, 2020.
A. Ahdiat, “Indonesia Punya UMKM Terbanyak di ASEAN, Bagaimana Daya Saingnya? [Indonesia Has the Most SMEs in ASEAN, How is its Competitiveness?],” Katadata, 2022. https://databoks.katadata.co.id/datapublish/2022/10/11/indonesia-punya-umkm-terbanyak-di-asean-bagaimana-daya-saingnya (accessed Nov. 01, 2022).
R. Gouvea et al., “The creative economy, innovation and entrepreneurship : an empirical examination,” Creat. Ind. J., vol. 0, no. 0, pp. 1–40, 2020, doi: 10.1080/17510694.2020.1744215.
Y. Lu, I. Bellos, B. N. Greenwood, and L. Huang, “Is it that You Can’t Learn, or You Won’t Learn? Technology-Enabled Monitoring and Heterogeneity in Sales Performance,” Technol. Monit. Heterog. Sales Perform. (April 6, 2022), 2022.
R. Wagner-Fabisch, C. Homburg, and A. Vomberg, “When does sales system agility lead to organizational performance?,” in AMA SUMMER ACADEMIC CONFERENCE, 2022, p. 766.
S. Wijaya, A. Andhika, and M. Ilyas, “Development of Sales Information System for SME with the Waterfall Method: A Grocery Store BSR Case,” J. Tek. Inform., vol. 3, no. 4, pp. 1043–1049, 2022.
C.-L. Yang and T. P. Q. Nguyen, “Sequential Clustering and Classification Approach to Analyze Sales Performance of Retail Stores Based on Point-of-Sale Data,” Int. J. Inf. Technol. & Decis. Mak., pp. 1–26, 2022.
A. Djakasaputra, O. Wijaya, A. Utama, C. Yohana, B. Romadhoni, and M. Fahlevi, “Empirical study of Indonesian SMEs sales performance in digital era: The role of quality service and digital marketing,” Int. J. Data Netw. Sci., vol. 5, no. 3, pp. 303–310, 2021.
A. Girardi, “Performance Measurement Systems Threatened by Pandemic Opportunities in Retail: How Managers Struggled to Balance Growing Sales With Unexpectedly Inadequate Supply Chain KPIs,” in Handbook of Research on Digital Innovation and Networking in Post-COVID-19 Organizations, IGI Global, 2022, pp. 137–151.
G. Wijaya, “Perancangan Data Warehouse Nilai Mahasiswa Dengan Kimball Nine-Step Methodology,” J. Inform., vol. 4, no. 1, 2017.
S. M. N. Huda and J. Sutrisno, “Analisa Perancangan Data Warehouse Dan Aplikasi Online Analytical Processing Pengajuan Kredit Pada PT Bfi Finance Indonesia, Tbk,” IDEALIS Indones. J. Inf. Syst., vol. 1, no. 3, pp. 354–359, 2018.
R. W. P. Kusumah, M. T. Tiur Gantini ST, and others, “Perancangan Data Warehouse Pada Bagian Akademik Universitas di Bandung,” J. Strateg. Maranatha, vol. 3, no. 1, pp. 194–205, 2021.
P. Subarkah, T. Astuti, D. Rakhmawati, P. Arsi, R. M. Anjani, and D. Fortuna, Data Warehouse dan Business Intelegence, vol. 1. Zahira Media Publisher, 2022.
I. Junaedi, D. Abdillah, and V. Yasin, “Analisis Perancangan Dan Pembangunan Aplikasi Business Intelligence Penerimaan Negara Bukan Pajak Kementerian Keuangan RI,” J. Inf. Syst. Applied, Manag. Account. Res., vol. 4, no. 3, pp. 88–101, 2020.
I. Sybase, “Business Intelligence in Half the Time (With Less Cost And Risk),” Data Warehous. Ultim. Guid. to Build. Corp. Bus. Intell., pp. 283–293, 2001.
H. Dresner, Profiles in performance: Business intelligence journeys and the roadmap for change. John Wiley & Sons, 2009.
C. Vercellis, Business intelligence: data mining and optimization for decision making. John Wiley & Sons, 2011.
A. A. Maziyyah, “Penggunaan Self-service Business Intelligence Dalam Pengambilan Keputusan di UMKM Pada Masa Pandemi Covid-19: Studi Kasus Toko Sayur Keluarga Yogyakarta [The Use of Self-Service Business Intelligence in Decision Making in SMEs During the Covid-19 Pandemic,” Universitas Islam Indonesia, 2022.
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