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Data-driven corporate growth: A dynamic financial modelling framework for strategic agility Sihotang, Hengki Tamando; Vinsensia, Desi; Riandari, Fristi; Chandra, Suherman
International Journal of Basic and Applied Science Vol. 13 No. 2 (2024): Sep: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v13i2.485

Abstract

This research aimed to develop a Dynamic Financial Growth Model (DFGM) to enhance corporate growth by promoting strategic agility through data-driven decision-making. The main objective was to optimize corporate value by integrating real-time data, dynamic decision-making, risk management, and scenario analysis. The research employed a mathematical modelling framework that combined predictive analytics, real options theory, and scenario-based optimization to represent dynamic corporate financial decisions. The numerical example demonstrated how the model adjusts strategic decisions in response to changes in market data and evaluates corporate value under optimistic, pessimistic, and baseline scenarios. The main results indicated that the DFGM is effective in optimizing corporate value by allowing for continuous adjustments and strategic flexibility, distinguishing itself from traditional static financial models that lack real-time adaptability. The findings highlighted the value of incorporating risk constraints and scenario analysis, resulting in a balanced approach that manages both growth and uncertainty. However, the study identified limitations, including the need for empirical validation, more complex predictive analytics, and accounting for behavioral factors affecting decision-making. The conclusion emphasizes that the DFGM provides an adaptable and data-driven framework that enhances corporate strategic agility, making it a valuable tool for managing growth in rapidly changing environments, while also suggesting future research to refine the model's practical application
Analysis of the Digital-Based Information System Learning Process on Student Readiness in the Digital Era Irwansyahputra, Muhammad; Syahputra, Muhammad Riza; Chandra, Suherman
Jurnal Mekintek : Jurnal Mekanikal, Energi, Industri, Dan Teknologi Vol. 16 No. 1 (2025): April: Mechanical, Energy, Industrial And Technology
Publisher : IHSA Institute

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Abstract

North Sumatra has several universities in various regions spread across 33 regencies/cities, where the number of students studying at several universities in North Sumatra according to the higher education database (PDDIKTI) is 130,182 students. As many as 25 percent of the number of students at several universities in North Sumatra who understand the use of information systems at the universities where they study, affect students' readiness to understand information system learning, which reduces students' understanding and knowledge, as well as their competence in knowing the contents of the material, understanding learning objectives, and understanding information system applications for decision making. This study aims to determine and analyze the extent to which the digital-based information system learning process influences students' readiness to understand learning using information systems in the digital era. The research method uses a quantitative descriptive method with a sampling technique using the accidental sampling method, and data collection techniques are carried out using observation, distributing questionnaires and documentation studies. The results of the study describe that the process of learning digital-based information systems has an effect on students' readiness in understanding learning information systems in the digital era, where students must be able to improve their knowledge, understanding and skills sufficiently by reading books and other literature, as well as increasing their applied knowledge about information systems in the digital era in order to be able and ready to improve their understanding of learning information systems.