Main Content
Open Access Articles

Business Intelligence and Decision Support to Enhance Decision-Making Quality in Higher Education

Main Article Content

  • Syamsiah Syamsiah1*
  • Agus Darmawan2
  • Halimatusa'diah Halimatusa'diah3
  • Reko Syarif Hidayatullah4
  • Nasrulloh Isnain5

Article Sidebar

Front Cover IJSECS VOLUME 5 NOMOR 2 AGUSTUS 2025

Abstract

The availability of accurate and reliable data is essential for organizational sustainability. Business intelligence (BI) enhances an organization's ability to analyze challenges, support decision-making, and improve performance. The term “Business Intelligence System” refers to applications and technologies that facilitate BI activities, including data collection, storage, access, and analysis—thus providing insights into performance and aiding informed decisions. These activities include decision support systems, querying, reporting, OLAP, statistical analysis, forecasting, and data mining. BI applications encompass reporting tools, analytics platforms, dashboards, alerts, and portals, and involve technologies such as data integration, quality management, warehousing, and content analysis. Accordingly, a Business Intelligence System can function as a Decision Support System. This study uses SPSS version 17 for data analysis to evaluate the impact of BI and decision support on decision-making quality in colleges in Jakarta and Bekasi. ANOVA (F-test) results show an F-value of 117.041, exceeding the F-table value of 3.29, with a significance of 0.000 < α = 0.05. Since the calculated F-value surpasses the critical value and the significance level is below 0.05, the null hypothesis is rejected. Thus, BI and decision support significantly and simultaneously influence decision-making quality (Y). These findings highlight the essential role of BI and decision support in improving decision-making within higher education institutions.

Article Details

How to Cite

Citation Format
Syamsiah, S., Darmawan, A., Halimatusa'diah, H., Hidayatullah, R. S., & Isnain, N. (2025). Business Intelligence and Decision Support to Enhance Decision-Making Quality in Higher Education. International Journal Software Engineering and Computer Science (IJSECS), 5(2), 510-518. https://doi.org/10.35870/ijsecs.v5i2.4273

References

27 References
  • Zarour, K., & Benmerzoug, D. (2019). A decision-making support for business process outsourcing to a multi-cloud environment. International Journal of Decision Support System Technology, 11(1), 66–92. https://doi.org/10.4018/IJDSST.2019010104
  • Ali, M. S., & Khan, S. (2019). Organizational capability readiness towards business intelligence implementation. International Journal of Business Intelligence Research, 10(1), 42–58. https://doi.org/10.4018/IJBIR.2019010103
  • Güngör-Demirci, G., Lee, J., Keck, J., Harrison, S. J., & Bates, G. (2019). Development of a risk-based tool for groundwater well rehabilitation and replacement decisions. Journal of Water Supply: Research and Technology-Aqua, 68(6), 411–419. https://doi.org/10.2166/aqua.2019.021
  • Hayajneh, S., & Harb, Y. (2023). Understanding the continuous use of business intelligence: The case of Jordan. Journal of Decision Systems, 1–32. https://doi.org/10.1080/12460125.2023.2253587
  • Huang, J.-C., Huang, H.-C., & Chu, S.-H. (2019). Research on image quality in decision management system and information system framework. Journal of Visual Communication and Image Representation, 63, 102588. https://doi.org/10.1016/j.jvcir.2019.102588
  • Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-making based on big data analytics for people management in healthcare organizations. Journal of Medical Systems, 43(9), 290. https://doi.org/10.1007/s10916-019-1419-x
  • Miah, S. J. (2021). Tailorable technologies for improving business intelligence systems. In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 814–829). IGI Global. https://doi.org/10.4018/978-1-7998-9023-2.ch039
  • Kirilov, L., Guliashki, V., & Staykov, B. (2021). Web-based decision support system for solving multiple-objective decision-making problems. In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 594–620). IGI Global. https://doi.org/10.4018/978-1-7998-9023-2.ch029
  • Esteves, M., Miranda, F., & Abelha, A. (2021). Pervasive business intelligence platform to support the decision-making process in waiting lists. In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 848–863). IGI Global. https://doi.org/10.4018/978-1-7998-9023-2.ch041
  • Wiwik, L., Dwiningrum, S. I. A., & Sujarwo, S. (2023). Decision support systems: A game changer in the field of education. AL-ISHLAH: Jurnal Pendidikan, 15(4). https://doi.org/10.35445/alishlah.v15i4.4245
  • Osuszek, L., & Ledzianowski, J. (2020). Decision support and risk management in a business context. Journal of Decision Systems, 29(sup1), 413–424. https://doi.org/10.1080/12460125.2020.1780781
  • Pereira, A. M., et al. (2022). Customer models for artificial intelligence-based decision support in fashion online retail supply chains. Decision Support Systems, 158, 113795. https://doi.org/10.1016/j.dss.2022.113795
  • Zarghami, S. A., & Zwikael, O. (2022). Measuring project resilience – Learning from the past to enhance decision making in the face of disruption. Decision Support Systems, 160, 113831. https://doi.org/10.1016/j.dss.2022.113831
  • Zhdanov, D., Bhattacharjee, S., & Bragin, M. A. (2022). Incorporating FAT and privacy aware AI modeling approaches into business decision-making frameworks. Decision Support Systems, 155, 113715. https://doi.org/10.1016/j.dss.2021.113715
  • Hsu, M.-F., & Lin, S.-J. (2021). A BSC-based network DEA model equipped with computational linguistics for performance assessment and improvement. International Journal of Machine Learning and Cybernetics, 12(9), 2479–2497. https://doi.org/10.1007/s13042-021-01331-7
  • Sujith, A. V. L. N., Qureshi, N. I., Dornadula, V. H. R., Rath, A., Prakash, K. B., & Singh, S. K. (2022). A comparative analysis of business machine learning in making effective financial decisions using structural equation model (SEM). Journal of Food Quality, 2022, 1–7. https://doi.org/10.1155/2022/6382839
  • Iftekhar, M. S., & Pannell, D. J. (2022). Developing an integrated investment decision-support framework for water-sensitive urban design projects. Journal of Hydrology, 607, 127532. https://doi.org/10.1016/j.jhydrol.2022.127532
  • Lennerholt, C., van Laere, J., & Söderström, E. (2023). Success factors for managing the SSBI challenges of the AQUIRE framework. Journal of Decision Systems, 32(2), 491–512. https://doi.org/10.1080/12460125.2022.2057006
  • Suboyin, A., Eldred, M., Thatcher, J., Rehman, A., Gee, I., & Anjum, H. (2023, January). Environomics framework for sustainable business practices: Industrial case studies on true impact reduction and process optimization through AI. In Day 1 Tue, 17 January 2023. SPE. https://doi.org/10.2118/214459-MS
  • Hmoud, H., Al-Adwan, A. S., Horani, O., Yaseen, H., & Al Zoubi, J. Z. (2023). Factors influencing business intelligence adoption by higher education institutions. Journal of Open Innovation: Technology, Market, and Complexity, 9(3), 100111. https://doi.org/10.1016/j.joitmc.2023.100111
  • Al-Surmi, A., Bashiri, M., & Koliousis, I. (2022). AI-based decision making: Combining strategies to improve operational performance. International Journal of Production Research, 60(14), 4464–4486. https://doi.org/10.1080/00207543.2021.1966540
  • Parsamehr, M., Perera, U. S., Dodanwala, T. C., Perera, P., & Ruparathna, R. (2023). A review of construction management challenges and BIM-based solutions: Perspectives from the schedule, cost, quality, and safety management. Asian Journal of Civil Engineering, 24(1), 353–389. https://doi.org/10.1007/s42107-022-00501-4
  • Maluleka, M. L., & Chummun, B. Z. (2023). Competitive intelligence and strategy implementation: Critical examination of present literature review. SA Journal of Information Management, 25(1). https://doi.org/10.4102/sajim.v25i1.1610
  • Tewari, A., Gabarro, J., Sole, J., Lapouble, B., & Montull, L. (2020). Artificial intelligence based decision making for venture capital platform. In Proceedings (pp. 136–149). https://doi.org/10.1007/978-3-030-46224-6_11
  • Yie, L. F., Susanto, H., & Setiana, D. (2021). Collaborating decision support and business intelligence to enable government digital connectivity. In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 830–847). IGI Global. https://doi.org/10.4018/978-1-7998-9023-2.ch040
  • Samihardjo, R., & Nugraha, U. (2020). Design of the Business Intelligence Dashboard for Sales Decision Making. International Journal of Psychosocial Rehabilitation, 24(2), 3498–3513. https://doi.org/10.37200/IJPR/V24I2/PR200670
  • Indriantoro, N., & Supomo, B. (2002). Metode penelitian bisnis. Yogyakarta: BPFE.

Author Biographies

Syamsiah Syamsiah, Indraprasta Pgri University

Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Agus Darmawan, Indraprasta Pgri University

Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Halimatusa'diah Halimatusa'diah, Indraprasta Pgri University

Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Reko Syarif Hidayatullah, Indraprasta Pgri University

Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Nasrulloh Isnain, Indraprasta Pgri University

Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Downloads

OJS UsageStats Plugin
Download data is not yet available.
Contrimetric

Recommended Articles