Implementation of a Sales Dashboard Using Metabase for Attendance Analysis and Sales Payroll Systems (Case Study: PT. Fiyansa)
##plugins.themes.bootstrap3.article.sidebar##
##plugins.themes.bootstrap3.article.main##
Galeh Ariya Irwana
https://orcid.org/0000-0003-1007-6888
Abstract
In an effort to adopt digital technology, PT. Fiyansa has developed an Android application to monitor sales activities. However, the data generated by this application remains difficult to analyze regarding attendance and is insufficient for supporting decision-making. The primary factor causing this issue is the lack of adequate visualization. To address this problem, this research develops a dashboard to visualize attendance analysis and the payroll system. This dashboard generates visualizations categorized into three groups: attendance summary, sales performance analysis, and sales payroll. The attendance summary category consists of six visualizations, the sales performance analysis category comprises nine visualizations, and the sales payroll category includes three visualizations: payroll details, the three salespeople with the lowest salaries, and the three salespeople with the highest salaries. The results obtained from the dashboard analysis indicate that the level of sales salaries is significantly influenced by work attendance. This is evidenced by the analysis showing that salespeople with the highest salaries tend to have high attendance rates and a low frequency of lateness.
Downloads
##plugins.themes.bootstrap3.article.details##
Copyright (c) 2025 Galeh Ariya Irwana, Rizqi Putri Nourma Budiarti
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
M. A. Zainuddin, S. Sukaridhoto, O. S. Hakim, and A. Prayudi, “Development of ERP System for Outsourcing Company using Internet of Things and Blockchain Technology,” JUITA: Jurnal Informatika, vol. 12, no. 2, pp. 227–234, Nov. 2024, doi: 10.30595/JUITA.V12I2.22059.
F. S. Utomo and Z. Lubna, “Sales Data Visualization to Determine Business Insight Using Metabase in a Global Retail Company,” SISTEMASI, vol. 13, no. 4, pp. 1402–1410, Jul. 2024, doi: 10.32520/STMSI.V13I4.3870.
M. A. A. E. Yousef and V. Dattana, “Auto Attendance Smartphones Application Based on the Global Positioning System (GPS),” Advances in Intelligent Systems and Computing, vol. 1363 AISC, pp. 917–934, 2021, doi: 10.1007/978-3-030-73100-7_63.
I. M. Putri, D. P. Ramadhani, P. Indriyani, E. N. Aidah, and A. P. Cahyani, “Predictive Analytics in Attendance Systems for Employee Productivity and Accountability,” International Transactions on Education Technology (ITEE), vol. 3, no. 2, pp. 104–113, Jan. 2025, doi: 10.33050/ITEE.V3I2.718.
T. Doan, N. Vuong, and L. T. Nguyen, “The Key Strategies for Measuring Employee Performance in Companies: A Systematic Review,” Sustainability 2022, Vol. 14, Page 14017, vol. 14, no. 21, p. 14017, Oct. 2022, doi: 10.3390/SU142114017.
J. Qian, “Application of Data Analysis in Employee Performance Management,” Learning and Analytics in Intelligent Systems, vol. 47, pp. 475–485, 2025, doi: 10.1007/978-3-031-85952-6_44.
M. Marchington, “Human resource management (HRM): Too busy looking up to see where it is going longer term?,” Human Resource Management Review, vol. 25, no. 2, pp. 176–187, Jun. 2015, doi: 10.1016/J.HRMR.2015.01.007.
D. P. Lepak and S. A. Snell, “Virtual HR: Strategic human resource management in the 21st century,” Human Resource Management Review, vol. 8, no. 3, pp. 215–234, Sep. 1998, doi: 10.1016/S1053-4822(98)90003-1.
S. Ahmad and R. G. Schroeder, “The impact of human resource management practices on operational performance: recognizing country and industry differences,” Journal of Operations Management, vol. 21, no. 1, pp. 19–43, Jan. 2003, doi: 10.1016/S0272-6963(02)00056-6.
H. I. Al Nsour and B. K. A. Tayeh, “The Impact of Talent Management on Competitive Advantage in Commercial Banks in Jordan from the Point of View of Banks’ Employees,” Arab Economic and Business Journal, vol. 13, no. 1, pp. 60–72, Jun. 2018, doi: 10.1016/J.AEBJ.2017.06.002.
Y. S. Chin, A. A. Mohamad, and M. C. Lo, “Harnessing the power of artificial intelligence (AI): a paradigm shift in HRM practices for employee sustainable performance,” Global Knowledge, Memory and Communication, 2024, doi: 10.1108/GKMC-06-2024-0355/1258000/HARNESSING-THE-POWER-OF-ARTIFICIAL-INTELLIGENCE-AI.
R. K. Gupta and C. M. Tembhurnekar, “AI-DRIVEN PERFORMANCE APPRAISAL SYSTEMS: A CRITICAL LITERATURE REVIEW OF EMERGING ISSUES AND CHALLENGES,” ShodhKosh: Journal of Visual and Performing Arts, vol. 5, no. 7, pp. 492-496–492–496, Jul. 2024, doi: 10.29121/SHODHKOSH.V5.I7.2024.3481.
Dr. K. P, “HR Analytics: Data-Driven Decision Making for Employee Performance Management,” South East Eur J Public Health, vol. 2, pp. 1820–1831, Dec. 2024, doi: 10.70135/SEEJPH.VI.2983.
P. M. Wright, “Introduction: Strategic human resource management research in the 21st century,” Human Resource Management Review, vol. 8, no. 3, pp. 187–191, Sep. 1998, doi: 10.1016/S1053-4822(98)90001-8.
N. Y. Oppong, “The seven myths of global talent management: A reflection,” Social Sciences & Humanities Open, vol. 8, no. 1, p. 100633, Jan. 2023, doi: 10.1016/J.SSAHO.2023.100633.
G. Cachón-Rodríguez, A. Blanco-González, C. Prado-Román, and C. Del-Castillo-Feito, “How sustainable human resources management helps in the evaluation and planning of employee loyalty and retention: Can social capital make a difference?,” Eval Program Plann, vol. 95, p. 102171, Dec. 2022, doi: 10.1016/J.EVALPROGPLAN.2022.102171.
C. Cayrat and P. Boxall, “The roles of the HR function: A systematic review of tensions, continuity and change,” Human Resource Management Review, vol. 33, no. 4, p. 100984, Dec. 2023, doi: 10.1016/J.HRMR.2023.100984.
A. Lercher, J. Glock, C. Macho, and M. Pinzger, “Microservice API Evolution in Practice: A Study on Strategies and Challenges,” Journal of Systems and Software, vol. 215, p. 112110, Sep. 2024, doi: 10.1016/J.JSS.2024.112110.
D. Sharma and A. Selwal, “A survey on face presentation attack detection mechanisms: hitherto and future perspectives,” Multimed Syst, vol. 29, no. 3, p. 1527, Jun. 2023, doi: 10.1007/S00530-023-01070-5.
F. Abdillah Ahmad, N. Pratiwi, M. D. Hamka, J. Timur, and P. DKI Jakarta, “Implementation of Face Recognition, Attendance Detection, and Geolocation using TensorFlow Lite and Google ML Kit in a Mobile Attendance Application,” SISTEMASI, vol. 14, no. 1, pp. 172–186, Jan. 2025, doi: 10.32520/STMSI.V14I1.4775.
M. C. Meyers, “The neglected role of talent proactivity: Integrating proactive behavior into talent-management theorizing,” Human Resource Management Review, vol. 30, no. 2, p. 100703, Jun. 2020, doi: 10.1016/J.HRMR.2019.100703.
G. Matthews, “Employee engagement: what’s your strategy?,” Strategic HR Review, vol. 17, no. 3, pp. 150–154, Jun. 2018, doi: 10.1108/SHR-03-2018-0025.
R. P. N. Budiarti, S. Sukaridhoto, U. Zuhdi, A. Rasyid, and A. I. Sonhaji, “Implementation of Big Data Information System Using Open-Source Metabase for Civil Registration and Vital Statistics Data Visualization in Surabaya,” JOIV: International Journal on Informatics Visualization, vol. 7, no. 4, pp. 2358–2365, 2023.
B. Santos et al., “Open source business intelligence tools: Metabase and redash,” in IC3K 2019 - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2019. doi: 10.5220/0008351704670474.
M. Sambrani, “Sales Dashboard Development for Business Performance Optimization,” 2023.