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All Journal International Journal of Social Service and Research Interdisciplinary Social Studies Novatio : Journal of Management Technology and Innovation Logistica : Journal of Logistic and Transportation
Widayat, Tri Agung
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation

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The Influence of Self-Efficacy, Knowledge, Attitude, and Skills on the Organizational Performance of the Ministry of Transportation, Mediated by Personnel Competence, Graduates of Indonesian Aviation Higher Vocational Education Widayat, Tri Agung; Arafah, Willy; Anggiani, Sarfilianty
International Journal of Social Service and Research Vol. 4 No. 03 (2024): International Journal of Social Service and Research (IJSSR)
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v4i03.752

Abstract

This research delves into the impact of various factors on Organizational Performance, with a specific focus on graduates of Vocational Higher Education in Aviation in Indonesia employed as Civil Servants (ASN) within the Ministry of Transportation. The factors under scrutiny include Self-efficacy, Knowledge, Attitude, and Skill, with an exploration of their positive influence on Organizational Performance. Furthermore, the study examines how these factors contribute to Personnel Competence among these graduates and assesses the resultant effect on Organizational Performance within the Ministry of Transportation. Additionally, it investigates the mediating role of Personnel Competence in the relationship between Self Efficacy, Knowledge, Attitude, Skill, and Organizational Performance. Employing a quantitative survey method with a positivistic approach, this study utilizes Structural Equation Modeling (SEM) for data analysis. Through this methodology, the research aims to elucidate the correlation between graduate competencies and organizational tasks. The ultimate goal is to provide valuable insights into bolstering organizational performance through effective human resource development strategies within the aviation sector, thereby catering to readers unfamiliar with the topic or research methods and ensuring clarity and coherence in the language to enhance understanding.
Business Analytics as a Strategic Resource for Innovation: A Comprehensive Review Juwari; Marthalia, Lia; Widayat, Tri Agung; Andrianto, Deny Tomy
Novatio : Journal of Management Technology and Innovation Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v2i2.1001

Abstract

This study provides a narrative review of the role of business analytics in driving organizational innovation performance. The purpose is to synthesize current empirical and theoretical contributions with a focus on organizational capabilities, market dynamics, leadership, culture, and global perspectives. Literature was identified through major databases (Scopus, Web of Science, PubMed, and IEEE Xplore) with inclusion criteria emphasizing peer-reviewed studies from the last decade. Findings highlight four key insights: organizational capabilities mediate the translation of analytics into innovation; market dynamism moderates its effectiveness; leadership and culture are decisive in embedding analytics; and adoption disparities persist between developed and developing economies. The review concludes that business analytics strengthens strategic agility and sustainable competitiveness, though barriers such as data quality, infrastructure, and ethics remain. Future research should explore longitudinal impacts, small and medium enterprises, and cross-country comparisons to optimize analytics-driven innovation.
Strategic Enablers of ROI in Data Driven Marketing: The Role of Leadership, Culture, and BI Maturity Widayat, Tri Agung; Toja, Andi Batari
Novatio : Journal of Management Technology and Innovation Vol. 3 No. 1 (2025): January 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v3i1.858

Abstract

This study investigates how data-driven marketing practices influence return on investment (ROI), focusing on the organizational enablers that shape their effectiveness. While the rapid growth of big data and analytics offers firms new opportunities, many struggle to translate these resources into measurable financial outcomes. This research addresses this gap by examining how leadership orientation, cultural readiness, and business intelligence (BI) maturity enhance the effectiveness of data-driven strategies in improving ROI.  Using a mixed-methods approach, the study combines survey data with illustrative case studies to uncover how firms align data strategies with performance outcomes. Case evidence, such as Hugo Boss’s €15 million investment in data infrastructure, is used to complement the quantitative results and illustrate practical relevance.  Findings show that predictive analytics and self-service BI can substantially increase ROI compared to traditional marketing methods. Their effectiveness is strengthened when supported by transformational leadership, a strong data culture, and organizational learning. Moreover, firms with mature BI systems demonstrate greater agility in responding to market changes, while competitive industry conditions further amplify the benefits of data-driven strategies. This study contributes a comprehensive model linking data strategies, organizational enablers, and financial performance. It offers practical insights for managers seeking to maximize the value of analytics investments through strategic alignment, cultural transformation, and committed leadershi.
Barriers and Opportunities in Circular Logistics: A Global Comparative Narrative Review Widayat, Tri Agung; Mintje, Quirina Ariantji Patrisia; Yosepha, Sri Yanthy
Logistica : Journal of Logistic and Transportation Vol. 2 No. 3 (2024): July 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/logistica.v2i3.1055

Abstract

This study reviews and synthesizes current knowledge on eco-efficient transport models within the frameworks of green logistics and the circular economy. The aim is to evaluate how technological, regulatory, and economic factors influence adoption and implementation. Literature was systematically gathered from major databases such as Scopus, Web of Science, and Google Scholar, using targeted keywords and Boolean search strategies. Inclusion criteria prioritized peer-reviewed articles published between 2018 and 2025 that addressed sustainable logistics, circular supply chains, and digital innovations. The review identified four major themes: drivers, barriers, case studies, and regional comparisons. Findings reveal that digital technologies, including artificial intelligence, blockchain, and the Internet of Things, enhance transparency, traceability, and efficiency. Regulatory frameworks, particularly in Europe, accelerate adoption, while economic incentives strengthen competitiveness. However, barriers persist, especially high initial costs, infrastructural deficits, and weak enforcement in developing economies. Case studies confirm measurable benefits, such as emission reductions and cost savings, while comparative analyses show significant regional disparities. The discussion emphasizes the importance of systemic alignment across policy, markets, and organizational culture to overcome these challenges. Future research is recommended to expand empirical evidence, develop standardized evaluation tools, and examine underrepresented regions. Overall, the review highlights the urgent need for integrated strategies that combine technology, regulation, and collaboration to advance sustainable logistics.
Enhancing Driver Stress Detection through Multimodal Integration of Eye Tracking and Physiological Signals Widayat, Tri Agung; Mintje, Quirina Ariantji Patrisia; Yosepha, Sri Yanthy
Logistica : Journal of Logistic and Transportation Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/logistica.v3i3.1147

Abstract

Driver stress poses significant risks to traffic safety, impairing attention, decision-making, and reaction time. Traditional monitoring methods often lack sensitivity. This study proposes and validates a novel multimodal framework that integrates synchronized eye-tracking and physiological data to significantly enhance the sensitivity and real-time accuracy of driver stress detection, addressing limitations of earlier unimodal approaches. Thirty licensed drivers participated in simulated driving tasks under baseline and stress-induced conditions. Eye-tracking metrics (pupil diameter, fixation duration, blink rate) and physiological signals (heart rate, skin conductance, heart rate variability) were collected. Data were synchronized and analyzed using Linear Discriminant Analysis (LDA) and other machine learning models to classify stress conditions. Under stress, pupil dilation increased by 20%, blink rate rose by 35%, and gaze spread narrowed, indicating visual tunneling. Physiologically, heart rate increased by 17%, skin conductance by 31%, and HRV decreased by 19%. The combined multimodal model achieved 91.4% classification accuracy, outperforming unimodal approaches. These results align with previous research showing that multimodal systems provide more reliable stress detection by integrating visual and autonomic markers. The findings highlight the system’s potential for real-time applications in Driver Monitoring Systems (DMS). Multimodal integration of eye-tracking and physiological signals enhances the sensitivity and reliability of driver stress detection. This approach offers a foundation for intelligent, adaptive DMS capable of improving road safety. Future work should focus on real-world validation and ethical implementation strategies. These findings demonstrate that multimodal integration provides a more comprehensive understanding of driver stress through complementary visual and autonomic indicators. The proposed framework forms a foundation for intelligent, adaptive Driver Monitoring Systems (DMS) capable of real-time stress recognition and proactive safety intervention.
The influence of competence on organizational performance in government institutions: A case study Anggiani, Sarfilianty; Widayat, Tri Agung; Fatonah, Feti
Interdisciplinary Social Studies Vol. 4 No. 1 (2024): Regular Issue: October-December 2024
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/iss.v4i1.756

Abstract

This study aims to determine the influence of personnel competence on organizational performance in government agencies. The data are collected and analyzed systematically. The results show that, in the Ministry of Transportation, higher competencies among state civil servants (ASNs) lead to improved employee performance and contribute positively to organizational outcomes. The research contributes to understanding the relationship between employee competence and organizational performance within government agencies, especially in the Department of Transportation. Moreover, longitudinal studies could be conducted to assess the long-term effects of personnel development programs on organizational performances over time. This study provides valuable insights for improving efficiency and effectiveness in public sector operations. The study also highlights the importance of investing in training and development programs to enhance employee competencies, ultimately leading to better service delivery and achievement of organizational goals.
Co-Authors Andrianto, Deny Tomy Daniel Happy Putra Feti Fatonah Marthalia, Lia Mintje, Quirina Ariantji Patrisia Sarfilianty Anggiani, Sarfilianty Toja, Andi Batari Willy Arafah, Willy Yosepha, Sri Yanthy