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Inkubis: Jurnal Ekonomi dan Bisnis
Published by Politeknik Siber Cerdika Internasional
ISSN : 27753913     EISSN : 27751848     DOI : 10.59261
Core Subject : Economy,
Economics, Econometrics & Finance
INKUBIS: Jurnal Ekonomi dan Bisnis is a scientific periodical published twice a year or 6 months. INKUBIS: Jurnal Ekonomi dan Bisnis is managed by the Politeknik Siber Cerdika Internasional which publishes scientific manuscripts in the family of economics and business
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekomomi dan Ekonometrika
Articles 200 Documents
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Digital Risk Culture and Cyber Resilience Advantage in Indonesian Data Center Providers: Firm Competitive Performance and the Moderating Effect of Organizational Risk Response Habit Permadi, Aditya Dyan; Wiradinata, Trianggoro; Kohardinata, Cliff
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.149

Abstract

Background: The rapid digitalization of critical infrastructure has increased exposure to cyber threats. While research on cybersecurity governance is growing, the mechanisms linking behavioral cybersecurity culture to sustained resilience, particularly in high-availability digital infrastructure like data centers, are underexplored. This study addresses this gap by exploring how Digital Risk Culture (DRC) drives Sustainable Cybersecurity Transformation (SCT) and generates Cyber Resilience Advantage (CRA), with Organizational Risk Response Habit (ORRH) as a boundary condition. Objective: The study investigates how DRC impacts CRA through SCT and examines the moderating role of ORRH. It uses Resource Advantage Theory to conceptualize DRC as behavioral capital, SCT as an orchestration mechanism aligned with the NIST Cybersecurity Framework, and CRA as a resilience-based outcome. Methods: A quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) tested the hypotheses with data from 125 cybersecurity decision-makers in Indonesian data centers. PLS-SEM was chosen for its predictive modeling capabilities and ability to handle interaction effects. Results: Findings show DRC significantly influences SCT (beta = 0.499, p < 0.001), and SCT strongly enhances CRA (beta = 0.735, p < 0.001). ORRH negatively moderates the DRC-SCT relationship (beta = -0.120), indicating that excessive routinization can weaken adaptive transformation. The model explains 30.5 percent of the variance in SCT and 54.0 percent in CRA. Conclusion: This study highlights that DRC strengthens SCT, which enhances CRA in Indonesian data centers. The non-significant moderating effect of ORRH suggests formal governance mechanisms may counter routine reactivity, offering insights for CIOs and risk managers in fostering resilience-oriented transformation.
MyPertamina Transaction Increase Strategy Through Optimizing Application Use at Gas Stations Based on Machine Learning Hutapea, Fresly Leo Chandra; Widianto, Sunu; Samidi, Samidi
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.150

Abstract

Background: The digital transformation in the energy sector is accelerating cashless payment adoption. MyPertamina, PT Pertamina's mobile payment platform, has been deployed across gas stations nationwide. However, only 5.65% of 1.3 million registered users (September 2024) are active, and only 11.5% qualify as loyal users (≥4 transactions/month). This performance gap, which exists between registered, active, and loyal users, is the focus of this study, as existing research has overlooked the role of gas station operational governance in shaping transaction behavior. Objective: This study aims to (1) identify factors influencing MyPertamina usage at DKI Jakarta gas stations, (2) develop a machine learning-based prediction model to classify transaction behavior (MyPertamina vs. cash), and (3) create a G-STIC framework to increase adoption, usage intensity, and loyalty. Methods: A quantitative case study using the CRISP-DM framework analyzed secondary POS transaction data from 8,000 transactions (5,200 MyPertamina; 2,800 cash) at DKI Jakarta gas stations (2024). Stratified sampling was used, and the models—Decision Tree, Gradient Boosted Trees, and Decision Stump—were evaluated based on accuracy, precision, and recall. Results: Gradient Boosted Trees achieved the highest accuracy (97.75%). Gas Station Type and Class showed the strongest correlations with MyPertamina usage, suggesting further investigation of the Gas Station Code correlation. Conclusion: MyPertamina adoption is influenced by operational governance and service standards. The G-STIC framework provides actionable strategies for increasing digital transaction adoption, contributing to both academic literature and managerial practice in the energy retail sector.
Digital Financial Literacy and Trust in Digital Payment Systems in Shaping Public Decisions to Use Digital Wallets for Daily Transactions Fania Nabila Lakadjo; Imelda Dian Rahmawati
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.143

Abstract

Background: As the digital economy grows rapidly, the use of digital payment solutions, notably digital wallets, has become more common in everyday financial activities. However, the level of digital financial knowledge and trust in digital payment systems significantly impacts individuals' choices to consistently engage with digital wallets. Objective: This investigation explores the extent to which proficiency in digital finance, along with trust in digital payment systems, affects users' willingness to rely on digital wallets for regular spending activities. Methods: The research follows a quantitative approach, collecting responses from 120 community residents via a questionnaire and processing the data using a multiple linear regression model. Results: Digital financial literacy and trust in digital payment systems significantly increase the likelihood of choosing a digital wallet for transactions, both individually and in combination (p = 0.000). Trust emerges as the dominant predictor (β = 0.717), while digital financial literacy (β = 0.336) reinforces rational decision-making in digital spending contexts. The regression model explains 60.1% of the variance in digital wallet usage decisions (R² = 0.601), indicating strong model fit. Conclusion: This study confirms that digital financial literacy and trust in digital payment systems are the two dominant determinants of digital wallet adoption for daily transactions in the general Indonesian public. Future research should expand the variable set to include perceived ease of use, social influence, and hedonic motivation and apply structural equation modeling (SEM) to test mediation and moderation paths.
Sustainable Production Optimization in Food MSMEs: A GVSM, SWOT, and AHP Approach Tukhas Shilul Imaroh; Agustinus Hariadi Djoko Purwanto; Sonny Indrajaya
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.144

Abstract

Background: Optimizing sustainable production for Micro, Small, and Medium Enterprises (MSMEs) in South Tangerang is essential to improve operational efficiency and competitiveness under resource constraints and increasing sustainability demands. Objective: This study aims to formulate and prioritize sustainable production optimization strategies for food-sector MSMEs by integrating Green Value Stream Mapping (GVSM), SWOT analysis, and the Analytic Hierarchy Process (AHP). Methods: This study employs a mixed-method case study approach on a food-processing MSME in South Tangerang. GVSM is used to identify process inefficiencies, SWOT to analyze strategic factors, and AHP to determine the priority of improvement strategies. Results: GVSM identified eight waste categories, with green waste (single-use plastics, high energy/gas consumption) and waiting time as the most critical. AHP analysis yielded the following criteria weights: Marketing (C1 = 0.32), Support (C2 = 0.24), Sustainability (C3 = 0.18), Technology (C4 = 0.15), and Efficiency (C5 = 0.11), with a Consistency Ratio (CR) ≤ 0.10 confirming valid pairwise judgments. The top-priority strategy was digital platform/e-commerce adoption (A1 = 0.48), followed by human resource training and external support (A2 = 0.32), and product innovation and sustainability (A3 = 0.20). Collaborative distribution ranked lowest due to high implementation complexity. Conclusion: The integrated GVSM–SWOT–AHP approach provides a practical framework for linking process improvement with strategic decision-making and supports MSMEs in enhancing efficiency, competitiveness, and environmental performance. This study contributes to MSME operations management literature by demonstrating that process-level diagnostic tools (GVSM) can be systematically integrated with strategic prioritization methods (SWOT–AHP).
Artificial Intelligence Adoption and Career Reconfiguration of Office Workers: The Mediating Role of Training and Organizational Support Dony Ari Nugroho
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.151

Abstract

Background: The development of artificial intelligence (AI) is fundamentally reshaping workforce structures, particularly for office workers whose task profiles are highly exposed to automation-driven transformation. As organizations integrate AI into operational systems, employees increasingly face shifts in task composition, skill requirements, and long-term career trajectories. Objective: This study aims to explore the impact of AI on career shifts within the office sector. Methods: By adopting a quantitative research method through surveys and secondary data analysis, this study examines how office workers respond to changes caused by the adoption of AI in their work environments. Results: The findings indicate that AI adoption significantly reshaped task profiles for 73% of respondents, particularly affecting routine data processing, administrative tasks, and scheduling activities. Multiple regression results show that skills training is the strongest predictor of career adaptation (beta = 0.412, p = 0.002), followed by organizational support (beta= 0.389, p = 0.005), openness to technology (beta= 0.367, p = 0.003), and readiness to change (beta = 0.298, p = 0.011). Together, these variables explain 61% of the variance in adaptive outcomes (R² = 0.61). Mediation analysis further confirms that training and organizational support significantly mediate the relationship between AI adoption and career shifts. Conclusion: AI's career impact is organizationally mediated rather than technologically predetermined. The study introduces career reconfiguration as a framework explaining intra-role task transformation, extending existing career mobility and job transition theories while highlighting the importance of institutional support for workforce adaptation in AI-integrated workplaces.
Generational Dynamic Convergence as a Mechanism for Reducing Intergenerational Friction Rendy Soewitoardjo; Thomas Stefanus Kaihatu; Christian Herdinata
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.158

Abstract

Background: As organizations play to the strength of generational diversity while working through challenges towards productivity and cohesion, generational diversity is a two-edged sword in the contemporary multigenerational workplace. Objective: This study seeks to create and validate the Generational Dynamic Convergence (GDC) construct that establishes the level of multigenerational diversity so as to diminish intergenerational friction and improve organizational performance in family-owned business in Surabaya, Indonesia. Methods: GDC encompasses four interconnected dimensions based on theories of social behavior, organizational culture, and generational identity: Environmental Perception, Innovation Implementation, Generational Inclusion, and Communication Styles. The reliability and relevance of the GDC dimensions are validated by an Exploratory Factor Analysis (EFA) of data from 120 family-owned businesses in Surabaya, Indonesia. Results: Results indicate that GDC has the ability to bridge the generational gap, promote cooperation, and can be the solution to generational friction by harnessing the respective strengths of Baby Boomers, Generation X, Millennials, and Generation Z and can, as such, serve as a catalyst in creating inclusive, adaptable, resilient, and high-performing organizational cultures. This can be avoided in future consideration as the framework can be extended to different geographical and organizational contexts, making the results and conclusions more generalisable and useful. Conclusion: This research is the first to both identify and validate the GDC construct through EFA and in doing so reveals four distinct dimensions of GDC and show that generational convergence can enhance collaboration, innovation and performance and simultaneously reduce intergenerational conflict.
Strategy of Traditional Blood Cockle Farming in Limau Kapas District, Riau Province: A Value Chain and Governance Framework Analysis Nyoto Nyoto; Irwan Effendi; Evi Deliana; Emilda Firdaus; Hanafi Hussin
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.167

Abstract

Background: The traditional blood cockle farm in Limau Kapas District, Riau Province, Indonesia, has high economic potency, yet it still needs to be developed. While it has great potential, this sector faces a range of long-held challenges (particularly vague regulations that hinder legal-based businesses and repeated claims of land ownership from local fishermen who often steal fish from harvests). Objective: To investigate the economic opportunities that can be achieved by adopting good governance and improving management capabilities. Methods: The research was conducted using the qualitative method, with observation, interviews, and a literature review. Results: The results suggest that improved governance can play a large role in alleviating these problems and increasing productivity. A collaborative effort between the government and the local community is key to developing a sustainable aquaculture ecosystem through education, favorable legislation, and access to capital for farmers. To gain those economic benefits of blood cockle aquaculture in the area, it is necessary to strengthen these aspects. Conclusion: In conclusion, traditional blood cockle farming in the Limau Kapas District has great economic prospects but is hindered by governance gaps, regulatory ambiguity and limited access to finance. Sustainable and equitable aquaculture development is possible only through effective institutional collaboration between government, universities, and local communities.
Leveraging AI for Individualized Outreach in Enrollment Marketing: A Study on Boosting University Application Intentions Isana Sri Christina Meranga
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.170

Abstract

Background: With the rise of Artificial Intelligence (AI) in higher education marketing, universities can reach prospective students in a more personalized manner. Nevertheless, only a few studies in the prevailing literature examine the dependence of students' enrollment decisions on trust and privacy perceptions regarding an institution's admission ability due to its AI-driven marketing, especially in an Indonesian setting. Objective: This study investigates the impact of AI marketing strategies on university application intentions of prospective students. Through the Stimulus-Organism-Response framework, it examines how AI content recommendation and interaction quality affect perceived trust and privacy risks, and subsequently, enrollment behavior. Method: This quantitative research employed purposive sampling, collecting data from 350 prospective students. The conceptual model was examined using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. Privacy calculus was included as a moderator to examine trade-offs between personalization advantages and data privacy risks. Results: All seven hypotheses received support, as both AI content recommendations and interaction quality have direct and indirect influences on university application intentions. Perceived trust had a strong mediation effect on content quality, while privacy risk had a strong mediation effect on AI interaction. Privacy calculus moderated the effect of privacy risk on application intention, indicating that high AI service utility can alleviate data-related concerns. Conclusion:This study extends higher education marketing literature by presenting a holistic perspective on the Privacy-Personalization Paradox. It identifies institutional trust and privacy calculus as critical psychological determinants of digital recruitment systems, and offers strategies for universities leveraging AI-based engagement tools.
Global Trends in Green Finance in the Banking Sector: A Bibliometric Mapping of Past and Future Research Directions Rusdi Hidayat Nugroho; Indah Respati Kusumasari; Nugraha Kusbianto; Nurhadi Nurhadi; Lusi Kurnia
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.166

Abstract

Background: This analysis is a systematic review of green finance in the banking sector, combining information from 193 papers published in 126 journals indexed in Scopus between 2020 and 2025. Objective: To provide a broad reference source for future research and a better understanding of the interaction between banks, environmental protection, climate change, and the 2030 Sustainable Development Goals. The most recent contributions in green banking—mitigation of risk, technology, credit policy, and ethical practices within organizations—are pointed out. Methods: Quantitative analysis based on bibliometric methodology of the Scopus database with search string TITLE-ABS-KEY("green finance") AND TITLE-ABS-KEY("bank" OR "banking"). Data screening followed the PRISMA framework (N₁=312 → N₂=246 → N₃=193). Bibliometric analysis was conducted using R 4.3.2 (Bibliometrix package) and VOSviewer 1.6.20 for keyword co-occurrence, co-authorship, and thematic mapping. Results: The review reveals five influencing factors and four main research thematic fields, addressing (i) what has already been investigated in green finance applied to banks, and (ii) what directions remain unexplored. The paper concludes with a forward-looking agenda to align green finance definitions and measurements across countries, integrate green risk into regulatory frameworks, incorporate it into credit decisions, and use technology to facilitate effective implementation of the emerging global landscape in green finance. Conclusion: Green finance in banking has gone from a conceptual framing to an empirical inquiry structured by laws and the regulatory regime. Research going forward needs to focus on cross-nation comparability, ethical governance of banks, climate-risk assessment in credit decisions, and fintech solutions for green finance channeled through banks—with a focus on developing economies like Indonesia.
The Efficiency-Equity Frontier: Optimal Allocation of Village Funds In Indonesia's Decentralized Governance Framework Wildan Maulana Assani Mualim; Ira Meiyenti; Arina Romarina; Ardieansyah Ardieansyah
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 1 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i1.169

Abstract

Background: Indonesia's Village Fund (Dana Desa) has disbursed Rp 608.9 trillion (≈ USD 35.8 billion) to 75,753 villages since 2015, yet whether this fiscal transfer simultaneously advances efficiency and equity in rural development remains an open empirical question. Spatial interdependencies among villages and heterogeneous local institutional capacities are rarely accounted for in existing evaluations. Objective: This study examines how Village Fund allocations navigate the efficiency–equity trade-off across Indonesian villages, quantifies spatial spillover effects on regional development outcomes, and develops evidence-based allocation algorithms to simultaneously advance efficiency and equity. Methods: We apply a Bayesian Spatial Durbin Model integrated with Generalized Random Forests to a balanced panel of 674,649 village-year observations (2015–2023). Identification draws on difference-in-differences with propensity score matching, regression discontinuity at population thresholds, and instrumental variables using pre-treatment geographic characteristics. Results: A 1% increase in Village Fund allocation reduces rural poverty by 0.152–0.183%, though this effect is contingent on local institutional capacity, with significantly larger gains among villages exceeding a capacity threshold of 0.65. Significant spatial spillovers (β = −0.089) indicate that investment in each village generates indirect poverty-reducing benefits for neighboring villages.The model explains 42.3% of outcome variation (R² = 0.423). Conclusions: The Village Fund considerably reduces rural poverty, but effectiveness is circumscribed by local institutional capacity—not merely village or fund size. Policymakers should prioritize capacity-building before scaling up allocations, and adopt performance-based formula adjustments that capitalize on spillover dynamics across village clusters.

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