Mathematical Logic as a Foundation for AI-Driven Decision-Making Systems

Tiurida Lily Anita; Rio Gilmer Freedy; Nur Silawati; Meriyana Sunengsih

Authors

Tiurida Lily Anita Bina Nusantara University Author https://orcid.org/0000-0003-0167-1204
Rio Gilmer Freedy Eduaward Incorporation Author
Nur Silawati University of Raharja Author https://orcid.org/0009-0001-6595-9365
Meriyana Sunengsih UR Mart Author https://orcid.org/0009-0002-6480-1571

Keywords:

Managerial Decision-Making, Logical Reasoning, Mathematical Logic, Structural Equation Modeling (SEM), Analytical Thinking

Abstract

Managerial decision-making plays a critical role in organizational success, often relying on logical reasoning to evaluate complex scenarios and devise effective strategies. As the Background of this study, the growing complexity of modern organizational environments and the increasing volume of data highlight the need for structured analytical frameworks such as mathematical logic to support more accurate and consistent decision-making. This research aims to achieve its Objective by examining how an understanding of propositional and predicate logic contributes to improving managerial capabilities in analyzing problems, developing strategies, and selecting effective solutions in various business contexts. Using a quantitative approach, the Method involves distributing a structured survey to 150 managers from diverse industries, measuring their understanding of mathematical logic and their perceived decision-making effectiveness, followed by an analysis using Structural Equation Modeling (SEM) to determine the strength and significance of the relationship between the variables. The findings provide Results showing that managers with higher levels of logical reasoning proficiency exhibit superior abilities in problem structuring, scenario evaluation, and solution implementation, indicating a strong positive correlation between mathematical logic comprehension and managerial decision-making effectiveness. The study concludes with a Conclusion emphasizing that integrating mathematical logic into managerial training programs can enhance analytical thinking, reduce cognitive biases, and ultimately strengthen organizational decision outcomes. Overall, the research underscores the practical importance of logical reasoning as a foundational competency for managers and suggests that organizations may benefit from incorporating logic-based frameworks into leadership development and decision-support systems.

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References

[1] G. M. Abashes, B. Elshqeirat, A. A. Abu-Shareha, and M. Alshraideh, “Beyond the noise: unveiling meaningful patterns in mobile payment data using fuzzy logic and svm,” J. Theor. Appl. Inf. Technol, vol. 103, no. 1, pp. 266–284, 2025.

[2] M. Choiri, E. S. Pramudito, F. Sutisna, and R. S. Sean, “Business artificial intelligence for enhancing sustainable decision intelligence,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 7, no. 1, pp. 106–116, 2025.

[3] A. Sutarman, R. Aprianto, R. Mitrev, R. Adyatama, and M. Yusup, “Influence of digital technology & data analytics on strategic decision making,” Startupreneur Business Digital (SABDA Journal), vol. 4, no. 1, pp. 12–23, 2025.

[4] J. Khalid, M. Chuanmin, F. Altaf, M. M. Shafqat, S. K. Khan, and M. U. Ashraf, “Ai-driven risk manage-ment and sustainable decision-making: Role of perceived environmental responsibility,” Sustainability, vol. 16, no. 16, p. 6799, 2024.

[5] D. Balisa, A. Leffia, Y. Shino et al., “Memanfaatkan fungsi sistem informasi manajemen: Prospek dan tantangan di dunia bisnis,” Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi, vol. 2, no. 2, pp. 123–133, 2024.

[6] H. Haryanto, A. Alvani, H. Azam, and S. Anyuniarwati, “Analisis big data dan bisnis intelegent melalui lensa baurang pemasaran pada industri manufaktur,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 5, no. 2, pp. 25–32, 2024.

[7] L. Broccardo, E. Ballesio, M. Z. Yaqub, and A. K. Mohapatra, “A bridge to success: the role of man-agement accountants’ intellectual capital in driving organizational decision-making through knowledge management,” Journal of Knowledge Management, vol. 29, no. 5, pp. 1365–1411, 2025.

[8] K. Mirdad, A. R. Dina, and R. Haris, “Analisis tren pasar dan pengambilan keputusan berbasis data dalam meningkatkan daya saing bisnis,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 5, no. 2, pp. 72–80, 2024.

[9] G. Nicola and R. Setiawan, “Creating competitive advantage through digital innovation: Insights from startupreneurs in e-commerce,” Startupreneur Business Digital (SABDA Journal), vol. 3, no. 2, pp. 131–140, 2024.

[10] W. Usino, D. A. R. Kusumawardhani, T. Ramadhan, A. Pratiangga, and O. Qurotulain, “Big data analyt-ics: Transforming business intelligence and decision making,” Journal of Computer Science and Technol-ogy Application, vol. 1, no. 2, pp. 154–163, 2024.

[11] E. Sediyono, K. D. Hartomo, Y. A. Susetyo, and A. Setiwan, “The intelligence decision making on asset management using fuzzy clustering,” in 2021 2nd International Conference on Innovative and Creative Information Technology (ICITech). IEEE, 2021, pp. 117–122.

[12] K.-H. Hu, F.-H. Chen, M.-F. Hsu, and G.-H. Tzeng, “Governance of artificial intelligence applications in a business audit via a fusion fuzzy multiple rule-based decision-making model,” Financial Innovation, vol. 9, no. 1, p. 117, 2023.

[13] U. Rahardja, Q. Aini, A. S. Bist, S. Maulana, and S. Millah, “Examining the interplay of technology readiness and behavioural intentions in health detection safe entry station,” JDM (Jurnal Dinamika Man-ajemen), vol. 15, no. 1, pp. 125–143, 2024.

[14] U. Rahardja, O. Candra, A. K. Tripathi, M. M. A. Zahra, B. S. Bashar, I. Muda, N. K. A. Dwijendra,

S. Aravindhan, and R. Sivaraman, “Mathematical modelling of engineering problems,” Journal home-page: http://iieta. org/journals/mmep, vol. 10, no. 2, pp. 727–732, 2023.

[15] T. D. TRAN, T. D. TRUONG, T. V. PHAM, and D. H. PHAM, “Cognitive competency, problem-solving skills and decision-making: a case study of students’ extracurricular activities in the distribution chains sector,” The Journal of Distribution Science (JDS), vol. 22, no. 2, pp. 71–82, 2024.

[16] M. H. R. Chakim, R. T. Utami, T. W. Sitanggang, A. Tanjung, A. Rizky, and E. A. Beldiq, “Innova-tion behavior research: Global trends and emerging themes in entrepreneurial business practices,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 3, pp. 574–585, 2024.

[17] B. E. Sibarani, C. Anggreani, B. Artasya, and D. A. P. Harahap, “Unraveling the impact of self-efficacy, computer anxiety, trait anxiety, and cognitive distortions on learning mind your own business: The student perspective,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 1, pp. 29–40, 2024.

[18] F. A. Rahardja, S.-C. Chen, and U. Rahardja, “Review of behavioral psychology in transition to solar photovoltaics for low-income individuals,” Sustainability, vol. 14, no. 3, p. 1537, 2022.

[19] A´ . Szukits, “The illusion of data-driven decision making–the mediating effect of digital orientation and

controllers’ added value in explaining organizational implications of advanced analytics,” Journal of man-agement control, vol. 33, no. 3, pp. 403–446, 2022.

[20] S. Tsyuh et al., “The influence of management creativity on the optimality of management decisions over time: An innovative aspect,” Journal of Eastern European and Central Asian Research, vol. 10, no. 3, 2023.

[21] H. Taherdoost and M. Madanchian, “Decision making: Models, processes, techniques,” Cloud Computing and Data Science, pp. 1–14, 2024.

[22] C. Lukita, A. W. A. Rahman, I. N. Hikam, and U. Rahardja, “Integrating strategic management with sdg 10 for sustainable development and equity,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 2, pp. 638–649, 2025.

[23] I. Sembiring, D. Manongga, U. Rahardja, and Q. Aini, “Understanding data-driven analytic decision making on air quality monitoring an empirical study,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 3, pp. 418–431, 2024.

[24] M. B. Karo, B. P. Miller, and O. A. Al-Kamari, “Leveraging data utilization and predictive analytics: Driv-ing innovation and enhancing decision making through ethical governance,” International Transactions on Education Technology (ITEE), vol. 2, no. 2, pp. 152–162, 2024.

[25] E. Susetyono, D. S. Priyarsono, A. Sukmawati, and P. Nurhayati, “Improving risk management maturity in ultra micro soe holding companies,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 310–324, 2026.

[26] S. Vudugula, S. K. Chebrolu, M. Bhuiyan, and F. Z. Rozony, “Integrating artificial intelligence in strategic business decision-making: A systematic review of predictive models,” International Journal of Scientific Interdisciplinary Research, vol. 4, no. 1, pp. 01–26, 2023.

[27] M. T. Mellaku and A. S. Sebsibe, “Potential of mathematical model-based decision making to promote sustainable performance of agriculture in developing countries: A review article,” Heliyon, vol. 8, no. 2, 2022.

[28] U. Rahardja, I. D. Hapsari, P. H. Putra, and A. N. Hidayanto, “Technological readiness and its impact on mobile payment usage: A case study of go-pay,” Cogent Engineering, vol. 10, no. 1, p. 2171566, 2023.

[29] T. Hariguna, U. Rahardja, and Sarmini, “The role of e-government ambidexterity as the impact of current technology and public value: an empirical study,” in Informatics, vol. 9, no. 3. MDPI, 2022, p. 67.

[30] I. Nica, C. Delcea, and N. Chirit, a˘, “Mathematical patterns in fuzzy logic and artificial intelligence for financial analysis: a bibliometric study,” Mathematics, vol. 12, no. 5, p. 782, 2024.

[31] U. Rusilowati, U. Narimawati, Y. R. Wijayanti, U. Rahardja, and O. A. Al-Kamari, “Optimizing human resource planning through advanced management information systems: A technological approach,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 1, pp. 72–83, 2024.

[32] R. E. A. A. Alsalhi, Y. Mustapha, and M. F. Hilmi, “Entrepreneurial and inclusive leadership in enhancing employee innovation in the uae oil and gas sector,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 114–124, 2026.

[33] N. S. Lubis, S. Hanafi, and S. Hidayat, “Enhancing educator performance through edupreneurship in international baccalaureate programs,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 2, pp. 343–359, 2025.

[34] R. D. Hadiwidjaja, A. I. Suroso, H. Siregar, and I. Sailah, “Performance paradigm: Entrepreneurial good university governance mediating leadership style in state universities,” Aptisi Transactions on Techno-preneurship (ATT), vol. 6, no. 3, pp. 492–508, 2024.

[35] W. Usino, M. M. Sari, F. P. Oganda, O. P. M. Daeli, and E. Smith, “Artificial intelligence integration for sustainable business model innovation insights from global startups,” Sundara Advanced Research on Artificial Intelligence, vol. 1, no. 2, pp. 82–89, 2025.

[36] J. Crawford and M. Jabbour, “The relationship between enterprise risk management and managerial judgement in decision-making: A systematic literature review,” International Journal of Management Reviews, vol. 26, no. 1, pp. 110–136, 2024.

[37] H. R. N. Azizah, T. G. Permatasari, A. Winarno et al., “The relevance of logical principles as the basis for scientific thinking in the development of management science: A systematic study,” Journal of Studies in Academic, Humanities, Research, and Innovation, vol. 2, no. 2, pp. 421–430, 2025.

[38] B. S. Riza, “Blockchain dalam pendidikan: Lapisan logis di bawahnya,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 1, no. 1, pp. 41–47, 2020.

[39] Q. Aini, N. Lutfiani, N. P. L. Santoso, S. Sulistiawati, and E. Astriyani, “Blockchain for education pur-pose: essential topology,” Aptisi Transactions on Management, vol. 5, no. 2, pp. 112–120, 2021.

[40] N. Nisha and M. Abouagwa, “Mathematics: The backbone of smart business decisions,” in Marketing Strategies for Total Quality Management in Hospitality Excellence. IGI Global Scientific Publishing, 2026, pp. 187–210.

[41] E. Arif, S. Suherman, and A. P. Widodo, “Analyzing public sentiment on digital banks in indonesia via social media x,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 253–267, 2026.

[42] M. Kamil, J. Rianto, and D. Suprayogi, “Management of deciding decision making final project advisor in optimizing learning,” Aptisi Transactions On Management, vol. 2, no. 2, pp. 168–176, 2018.

[43] Y. Zhang, Z. Li, Y. Sha, and K. Yang, “The impact of decision-making styles (effectuation logic and causation logic) on firm performance: a meta-analysis,” Journal of Business & Industrial Marketing, vol. 38, no. 1, pp. 85–101, 2023.

[44] M. Vasuki, A. D. Kumar, M. Celestin, and T. A. H. Alghazali, “Mathematical logic as the engine of autonomous decision intelligence in digital systems,” International Journal of Applied and Advanced Scientific Research, vol. 10, no. 2, pp. 97–108, 2025.

[45] Q. Aini, H. D. Purnomo, I. Setyawan, D. Manongga, U. Rahardja, I. Sembiring, S. Maulana et al., “The effect of perceived costs on blockchain adoption intention: an empirical study,” in 2023 11th International Conference on Cyber and IT Service Management (CITSM). IEEE, 2023, pp. 1–6.

[46] A. Ruangkanjanases, A. Khan, O. Sivarak, U. Rahardja, and S.-C. Chen, “Modeling the consumers’ flow experience in e-commerce: The integration of ecm and tam with the antecedents of flow experience,” SAGE Open, vol. 14, no. 2, p. 21582440241258595, 2024.

[47] Q. Aini, I. Sembiring, A. Setiawan, I. Setiawan, and U. Rahardja, “Perceived accuracy and user behavior: Exploring the impact of ai-based air quality detection application (aiku),” Indonesian Journal of Applied Research (IJAR), vol. 4, no. 3, pp. 209–224, 2023.