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Aptisi Transactions on Management
Published by Pandawan Sejahtera Indonesia
ISSN : 26226812     EISSN : 26226804     DOI : 10.33050/atm
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Aptisi Transactions on Management (ATM) adalah jurnal ilmiah yang diterbitkan oleh APTISI (Asosiasi Perguruan Tinggi Swasta Indonesia), guna memfasilitasi hasil jurnal ilmiah Civitas Akademika dalam bidang teknologi informasi, komunikasi, dan manajemen dalam menghadapi era digital di Indonesia. ATM terbit tengah tahunan (2 kali dalam setahun, periode Januari dan Juli).
Arjuna Subject : -
Articles 231 Documents
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A Study of Job Demands Resources as Antecedents of Educators Engagement in Universities Rony Setiawan; Kezia Kurniawati Nursalin; Ariesya Aprillia
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2631

Abstract

The performance of educational institutions is closely linked to the quality of lecturers’ work, which is largely influenced by their professionalism and work attitudes, particularly job engagement. High levels of job engagement encourage lecturers to contribute actively and demonstrate sustained dedication in their roles. Drawing on empirical evidence, this study examines the effects of Job Demands (JD) and Job Resources (JR) on lecturers’ Job Engagement (JE), while also exploring the moderating role of personal characteristics. This study adopts a quantitative approach using regression analysis and a univariate General Linear Model (GLM) to test both direct and interaction effects. The findings, based on data collected from 41 lecturers at a private university in Bandung, indicate that job demands negatively affect job engagement, whereas job resources have a positive effect. Furthermore, personal characteristics such as tenure, side job ownership, and cognitive style dimensions (information seeking and worldview) significantly influence the relationship between JD, JR, and JE. These results suggest that the dynamics of the Job Demands–Resources (JD-R) model are not universal but vary according to career stage and individual cognitive preferences. Practically, the study highlights the importance of adopting adaptive and individualised management strategies in balancing job demands and enhancing job resources to sustain lecturers’ engagement and academic performance in higher education contexts.
Data Driven and Sustainable Innovation Strategies for Long Term Product Market Fit in SMEs Sri Lestari Pujiastuti; Nanda Septiani; Adam Faturahman; Steven Harazaki Lase; Mitra Trima Dessincer Putri; April Lansonia
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2615

Abstract

In an increasingly dynamic and sustainability-conscious marketplace, startups and SMEs face mounting pressure to sustain product relevance and strategic resilience over time. This study investigates how integrated data-driven strategies support long-term product–market fit (PMF) through the alignment of real-time analytics, structured customer feedback loops, and sustainability-oriented innovation practices. Drawing on Resource-Based and Organizational Capability perspectives, the study conceptualizes digital capability formation as a strategic asset that strengthens adaptive market alignment under structural constraints. Using PLS-SEM analysis on data collected from 110 SMEs, five key constructs are examined: technology utilization, data-driven decision-making, customer feedback integration, sustainable innovation capability, and market responsiveness. The results indicate that technology utilization and data-driven decision-making exert significant positive effects on long-term PMF, while customer feedback integration facilitates iterative product refinement and market consistency. However, sustainable innovation capability and market responsiveness demonstrate negative path coefficients, suggesting that without structured governance, digital maturity, and prioritization mechanisms, these capabilities may generate operational strain or reactive strategic behavior that weakens long-term positioning. The findings extend the Data Strategy–Sustainability convergence literature by validating an integrative model that bridges digital capability development and responsible innovation in SME contexts. Managerially, the study highlights the importance of phased digital adoption and disciplined sustainability integration to ensure durable competitive alignment within evolving industrial ecosystems
Equity and Government Bond Relationship in Indonesia During Covid Pandemic Gracia Shinta S. Ugut; Liza Handoko; Kristina Vaher
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2619

Abstract

This study extends prior Covid-19 finance literature by examining the dynamic relationship between Indonesian equity returns and sovereign benchmark bond returns using daily data across two pandemic waves. Unlike previous studies focusing primarily on developed markets or conventional flight-to-safety behavior, this study provides evidence that government bonds in emerging markets may temporarily exhibit equity-like risk characteristics during pandemic-induced fiscal stress. Specifically, the findings show that equity market performance is positively correlated with government bond returns in Indonesia during the two waves of the Covid 19, as opposed to the findings from previous studies when there were financial crises, and also the results show negative correlation between the government bond return and the spread of the Credit Default Swap. Furthermore, this study examines the impact of the Covid pandemic to the local Indonesian long-term and medium-term benchmark bonds after applying the international risk factor variable to the model. The results show shifting investors’ attention from the international risk factors to the local risk factors in both medium and long tenor of the bonds during the pandemic period. Overall, this study highlights how pandemic-induced fiscal uncertainty alters stockbond dynamics in emerging markets and challenges conventional safe-haven assumptions regarding sovereign bonds.
Blockchain Financial Identity for Inclusive Access in Developing Nations Sutama Wisnu Dyatmika; Untung Rahardja; Muhtarom Muhtarom; Dwi Nur Ramadhan; Po Abbas Sunarya; Lily Maria Evans
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2621

Abstract

The absence of formal financial identity remains a significant barrier to financial inclusion in developing nations, limiting access to essential financial services. Traditional centralized identity systems are often vulnerable to data breaches, fraud, and institutional control, resulting in low public trust. This study aims to explore how blockchain-based identity systems, particularly through the concept of Self-Sovereign Identity (SSI), can address these limitations. The research adopts a qualitative case study approach by analyzing multiple blockchain-based digital identity initiatives across developing regions. The findings reveal that blockchain-enabled SSI enhances data security, transparency, and user autonomy, while improving accessibility to financial services. The key contribution of this study lies in identifying the integration of decentralized identity frameworks as a sustainable solution to strengthen financial inclusion and institutional trust. However, challenges such as infrastructure limitations, scalability issues, and regulatory uncertainty remain critical barriers. This study provides both theoretical insights and practical implications for policymakers, developers, and financial institutions in implementing secure and inclusive digital identity systems.
Audit Driven Evaluation of Carrier Style Memory Malware Detection Under Obfuscation and Adversarial Attacks Syamsu Hidayat; Kusrini Kusrini; Ema Utami; Arief Setyanto; Kristina Vaher
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2632

Abstract

This study evaluates Carrier-style memory malware detection under obfuscation using a reproducible, audit-driven protocol for verifiable reporting. We reproduce a stacking pipeline (Naive Bayes, Random Forest, Decision Tree with a Logistic Regression meta-learner) and benchmark it against strong single-model baselines. To limit leakage, we apply exact deduplication, train-only preprocessing, and group-disjoint splitting with explicit overlap checks, and we report dataset difficulty diagnostics to interpret near-ceiling results. Transfer is tested via cross-collection evaluation on the shared feature intersection between Obfuscated MalMem2022 and MemMalDet 2024, separating a low-shift validation setting from a higher-shift stress setting to keep generalization claims bounded. Robustness is assessed under a feasibility-preserving feature-space threat model with empirical bounds, non-negativity, and integer rounding, using a coordinate-search attack on the clean-correct subset across L0 budgets B=1,3,5, and 10 with confidence intervals. On obfuscated MalMem2022, Random Forest achieves 99.99% Accuracy, 99.99% F1, and 1.00 AUC, while the Carrier-style stack reaches 99.92% Accuracy, 99.92% F1, and 1.00 AUC, with no meaningful improvement over the best single model. Cross-collection validation yields F1 = 99.98 and AUC = 1.0, consistent with low-shift stability under aligned features rather than broad domain generalization. At B=10, ASR is 0.03 (95% CI: 0.0138–0.0639), and baseline defenses show clean-versus-robust trade-offs without consistent ASR reduction. We release four reusable artifacts an audit table, a leakage ablation matrix, a shift-aware cross-collection report, and robustness curves with confidence intervals.
Artificial Intelligence Driven Predictive Risk Management in Green Technology Investment Paroli Paroli; Agung Rizky; Qurotul Aini; Dwi Cahyono; Jonathan Parker; Untung Rahardja
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2635

Abstract

This study explores predictive risk management in green technology investments by leveraging Artificial Intelligence (AI) to address uncertainties associated with sustainable projects. As global financial institutions and governments increasingly allocate capital toward renewable energy, smart infrastructure, and low-carbon innovation, investors face multidimensional risks, including market volatility, technological failure, and regulatory change. Therefore, this research aims to develop an AI-driven predictive framework capable of identifying, analyzing, and forecasting potential investment risks in green technology portfolios to support informed decision-making. The study employs a quantitative approach using machine learning algorithms, including Random Forest, Gradient Boosting, and Neural Networks, trained on historical financial indicators, environmental performance metrics, and policy datasets. Each algorithm is selected based on its strengths: Random Forest for robustness, Gradient Boosting for predictive accuracy, and Neural Networks for capturing complex nonlinear relationships. A comparative perspective is used to highlight their tradeoffs, followed by feature importance analysis and predictive validation through cross-validation and evaluation metrics such as accuracy, precision, and RMSE. The findings show that the proposed model improves early risk detection compared to conventional statistical models, highlighting the effectiveness of machine learning in handling complex sustainability data. Furthermore, it identifies key risk determinants and enhances predictive reliability. Consequently, integrating AI-based predictive analytics into green investment strategies can strengthen risk mitigation, improve investor confidence, and support sustainable financial decision-making.
Trust Based Social Commerce Price and Consumer Behavior in Jastip Indonesia Suryari Purnama; Cicilia Sriliasta Bangun; Ramiro Santiago Ikhsan
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2636

Abstract

The rapid growth of social commerce in Indonesia has given rise to informal digital business models such as Jastip (Jasa Titip) personal shopping service, which represents a grassroots form of digital transformation among Micro, Small, and Medium Enterprises (SMEs). Operating entirely through digital platforms such as Instagram and WhatsApp, Jastip exemplifies how technology- driven commerce is reshaping consumer behavior and SME competitiveness beyond formal marketplace structures. This study empirically examines the influence of three key digital commerce antecedents, Online Customer Review (OCR), Shopping Experience (SE), and price on Online Purchase Intention (OPI), mediated by Consumer Trust (CT), in the Jastip context. A quantitative approach was employed using Structural Equation Modeling (SEM-LISREL) with 115 respondents from Generation Y (aged 24–39 years). Results demonstrate that price is the only antecedent with a significant direct effect on consumer trust (t-value = 2.84), which in turn strongly predicts online purchase intention (t-value = 5.76). Consumer trust fully mediates the price purchase intention relationship (complete mediation), while OCR and shopping experience were not found to significantly predict trust in this informal digital commerce context. These findings offer strategic implications for Jastip operators and digital SME policymakers, emphasizing that transparent pricing and trust architecture are the primary digital levers for driving purchase intention in informal social commerce platforms.
Integrating Video Storytelling Strategies in Recent Curriculum Implementation to Enhance Social Media Audience Engagement Aswadi Jaya; Sherli Triandari; Fhia Amelia; Ramzi Zainum Ikhsan; Ariana Delhi; Nuke Puji Lestari Santoso
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2637

Abstract

The rapid growth of social media has transformed digital communication practices and influenced recent curriculum implementation in digital learning and communication studies. Video-based content has become an important medium for delivering educational and promotional messages because it combines visual, audio, and narrative elements that enhance audience attention and emotional engagement. However, the increasing volume of social media content creates intense competition, requiring adaptive communication strategies to improve interaction effectiveness. One widely applied approach is video storytelling, which delivers messages through structured and meaningful visual narratives. This study aims to analyze the integration of video storytelling strategies in recent curriculum implementation to enhance social media audience engagement, measured through indicators such as likes, comments, shares, and watch duration. This research applies a descriptive qualitative method supported by engagement analytics through observation of video storytelling content, documentation of interaction metrics, and literature review. This study proposes a platform-adaptive storytelling framework that explains differences in engagement patterns across TikTok, Instagram, and YouTube by emphasizing narrative structure, emotional engagement, and platform suitability. The findings show that concise storytelling, emotional appeal, visual consistency, and alignment with platform characteristics significantly influence audience interaction and retention. The study concludes that integrating video storytelling strategies into recent curriculum implementation provides an effective digital communication approach for improving audience engagement and supporting adaptive learning and communication practices in contemporary social media environments.
Price Sensitivity and Switching Intention in Mobile Broadband Services Sylvia Samuel; Daniel Widjaja; Thomas Green
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i2.2638

Abstract

The rapid growth of digital connectivity has intensified competition in the mobile broadband industry, increasing the importance of understanding factors that influence customer switching behavior. Although prior studies have examined switching intention in telecommunications services, limited research has simultaneously investigated the roles of brand perception, price sensitivity, and service quality while considering demographic heterogeneity. This study examines the effects of brand perception, price sensitivity, and service quality on switching intention in the mobile broadband sector and evaluates the moderating role of gender. A quantitative survey was conducted among 153 mobile broadband users, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that price sensitivity significantly increases switching intention, indicating that consumers who are more responsive to price differences are more likely to change service providers. In contrast, brand perception and service quality do not significantly influence switching intention, suggesting that mobile broadband services are increasingly perceived as technologically homogeneous across providers. Furthermore, gender does not moderate the relationships between the key determinants and switching intention, although it shows a significant direct effect. These findings highlight the dominant role of economic evaluation in switching decisions and provide strategic implications for telecommunications providers in developing competitive pricing and customer retention strategies.
Financial Access and Saving Behavior in Women Entrepreneurship Development Zoel Hutabarat; Noah Rangi
APTISI Transactions on Management (ATM) Vol 10 No 3 (2026): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i3.2647

Abstract

Women-owned businesses have become an important driver of economic growth, employment generation, and social inclusion, particularly in developing countries. Despite their growing contribution, women entrepreneurs continue to encounter barriers related to financial access, institutional support, and entrepreneurial capabilities. This study investigates how business support, access to finance, skill development, and saving behavior influence women entrepreneurship development among small and medium-sized enterprises in Batam City, Indonesia. Data were obtained from 244 women entrepreneurs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The empirical results demonstrate that business support, financial access, and skill development positively affect women entrepreneurship development, with skill development emerging as the strongest predictor. In addition, saving behavior significantly moderates the relationship between access to finance and women entrepreneurship development, indicating that financial management practices influence the effectiveness of financial resources in supporting entrepreneurial growth. These findings suggest that sustainable women entrepreneurship depends on the interaction between external support mechanisms and individual entrepreneurial capabilities. The study provides practical implications for policymakers and entrepreneurship support institutions by emphasizing the importance of integrated strategies that strengthen financial inclusion, entrepreneurial competencies, financial literacy, and institutional support to foster the long-term development of women-owned enterprises.

Page 23 of 24 | Total Record : 231

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