Article Per Year (5 Year)
p-Index From 2021 - 2026
1.768
P-Index
This Author published in this journals
All Journal Journal of Applied Business and Technology Reflection: Education and Pedagogical Insights Luxury: Landscape of Business Administration
Kristy Veronica
Institut Bisnis dan Teknologi Pelita Indonesia, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
Exploring the Meaning of Employee Loyalty through the Lens of Organizational Behavior: A Phenomenological Study in Digital Start-up Firms Intan Purnama; Nicholas Renaldo; Harry Patuan Panjaitan; Achmad Tavip Junaedi; Suhardjo Suhardjo; Kristy Veronica
Journal of Applied Business and Technology Vol. 6 No. 1 (2025): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v6i1.226

Abstract

This study explores the lived experiences of employee loyalty within digital start-up firms from the perspective of organizational behavior. In an era where employee retention and engagement are critical, especially in dynamic digital start-up environments, understanding how loyalty is formed and interpreted by individuals becomes vital. Using a qualitative phenomenological approach, in-depth interviews were conducted with employees from various Indonesian digital start-ups to uncover the underlying meanings and personal interpretations of loyalty. The findings reveal that employee loyalty is perceived as a complex, evolving construct influenced by emotional attachment, shared values, autonomy, and mutual commitment. Loyalty was not merely transactional or tenure-based, but rather closely linked to personal growth, identity, and value alignment, especially among Millennial and Gen Z employees. This study contributes to organizational behavior literature by offering a nuanced view of loyalty that transcends traditional models, emphasizing the importance of intrinsic motivation and purpose-driven work in fostering long-term commitment. The results also offer practical implications for digital start-up leaders to cultivate environments that support psychological engagement, employee well-being, and sustainable loyalty.
Stakeholders’ Perspectives on Banking Support and Digital Accounting Adoption in the Palm Oil Industry Harry Patuan Panjaitan; Nicholas Renaldo; Achmad Tavip Junaedi; Nyoto Nyoto; Jahrizal Jahrizal; M Dalil; Dodi Sofyan Arief; Fifi Puspita; Rebecca La Volla Nyoto; Kristy Veronica
Luxury: Landscape of Business Administration Vol. 3 No. 2 (2025): Luxury: Landscape of Business Administration
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/luxury.v3i2.135

Abstract

This study aims to investigate how stakeholders, including palm oil enterprises, smallholder cooperatives, banking institutions, and regulators, perceive the role of banking support in facilitating or hindering the adoption of digital accounting systems. This study employs a qualitative exploratory design to capture the diverse perspectives of stakeholders on the role of banking support in facilitating digital accounting adoption within the palm oil industry. A purposive sampling strategy will be employed to ensure participants possess direct experience with either banking support or digital accounting adoption. Data will be analyzed using thematic analysis. Interview transcripts, focus group notes, and documents will be coded inductively and deductively, guided by the research questions. The findings reveal that banks are not merely providers of financial capital but also act as institutional gatekeepers that shape reporting practices and encourage digital transformation. Larger enterprises view digital accounting as a strategic tool for efficiency and compliance, while smallholders often see it as a burdensome requirement.
Smart Processing Machines and Business Efficiency in Goat Milk Agro-Enterprises Achmad Tavip Junaedi; Harry Patuan Panjaitan; Nicholas Renaldo; Nyoto Nyoto; Jahrizal Jahrizal; M Dalil; Jaswar Koto; Sulaiman Musa; Nabila Wahid; Kristy Veronica; Umar Faruq
Luxury: Landscape of Business Administration Vol. 3 No. 2 (2025): Luxury: Landscape of Business Administration
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/luxury.v3i2.137

Abstract

The increasing demand for functional and health-oriented dairy products has positioned goat milk agro-enterprises as a promising business sector, particularly in emerging economies. Despite this potential, many goat milk businesses face persistent challenges related to production inefficiency, high operational costs, and limited scalability. This study aims to examine the impact of smart processing machines on business efficiency in goat milk agro-enterprises. Using a quantitative approach, data were collected from small and medium-sized goat milk processing enterprises and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that smart processing machine adoption has a positive and significant effect on business efficiency, including cost efficiency, productivity, and operational effectiveness. The findings indicate that smart processing machines function not merely as technological tools but as strategic business resources that enhance operational performance and competitiveness. This study contributes to the business and agribusiness literature by providing empirical evidence at the production-machine level and highlighting the strategic value of smart manufacturing technologies in small-scale agro-enterprises. The findings offer practical insights for business owners, policymakers, and technology developers in promoting sustainable and efficient goat milk processing businesses.
Big Data Analytics for Demand Forecasting in the Mushroom Supply Chain Nicholas Renaldo; Kristy Veronica; Achmad Tavip Junaedi; Suhardjo Suhardjo; Amries Rusli Tanjung; Sri Indrastuti; Wilda Susanti; Jaswar Koto; Sulaiman Musa; Nabila Wahid
Luxury: Landscape of Business Administration Vol. 4 No. 1 (2026): Luxury: Landscape of Business Administration
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/luxury.v4i1.138

Abstract

The mushroom industry plays an increasingly important role in the agri-food sector due to rising demand for nutritious, functional, and sustainable food products. However, the mushroom supply chain faces significant challenges related to perishability, short shelf life, and demand uncertainty, which often result in inventory losses and inefficiencies. This study examines the role of big data analytics capability in enhancing demand forecasting accuracy and its impact on supply chain performance within the mushroom industry. Using a quantitative explanatory research design, data were collected through a structured questionnaire survey of mushroom supply chain actors, including producers, processors, distributors, and retailers. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that big data analytics capability has a significant positive effect on demand forecasting accuracy and supply chain performance. Furthermore, demand forecasting accuracy partially mediates the relationship between big data analytics capability and supply chain performance. These findings highlight the strategic importance of data-driven forecasting in managing demand uncertainty and improving operational efficiency in perishable agribusiness supply chains. This study contributes to the literature by extending big data analytics and demand forecasting research to the mushroom industry, providing both theoretical insights and practical implications for enhancing supply chain sustainability and competitiveness.
Learning Smart Farming through IoT Prototypes, Educational Impacts of Smart Goat Housing Systems in Vocational Education Achmad Tavip Junaedi; Nicholas Renaldo; Wilda Susanti; Rangga Rahmadian Yuliendi; Wahyu Joni Kurniawan; Yulvia Nora Marlim; Kristy Veronica; Harry Patuan Panjaitan; Umar Faruq; Jahrizal Jahrizal
Reflection: Education and Pedagogical Insights Vol. 3 No. 1 (2026): Reflection: Education and Pedagogical Insights
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/reflection.v3i1.141

Abstract

This study investigates the educational impacts of learning smart farming through Internet of Things (IoT)-based smart goat housing systems in vocational education. The rapid digital transformation of agriculture has created a growing demand for graduates with strong technological and applied competencies; however, the integration of real smart farming technologies into vocational curricula remains limited. To address this gap, this research employed a quasi-experimental design with a pretest–posttest non-equivalent control group to compare IoT prototype-based learning with conventional instructional approaches. The study involved vocational students enrolled in agriculture-related programs, where the experimental group engaged in project-based learning using an operational IoT-enabled smart goat housing system, while the control group received traditional instruction. The findings indicate that students exposed to IoT prototype-based learning demonstrated significantly higher improvements in digital competence, applied learning outcomes, and learning engagement compared to those in the control group. Qualitative insights further revealed that authentic interaction with real-time data and automated systems enhanced students’ understanding, motivation, and confidence in using digital technologies. These results highlight the pedagogical value of integrating real IoT prototypes into vocational education and confirm the effectiveness of experiential and technology-enhanced learning approaches in developing workforce-relevant competencies. This study contributes to vocational education literature by positioning livestock-based smart farming systems as effective learning media for digital agriculture education.
Developing Social Accounting Competencies through IoT-Based Goat Farming Learning Systems Suhardjo Suhardjo; Nicholas Renaldo; Achmad Tavip Junaedi; Kristy Veronica; Harry Patuan Panjaitan; Onny Setyawan; Wilda Susanti; Rahma Widi; Umar Faruq; Jahrizal Jahrizal
Reflection: Education and Pedagogical Insights Vol. 3 No. 1 (2026): Reflection: Education and Pedagogical Insights
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/reflection.v3i1.142

Abstract

The digital transformation of agriculture has created new opportunities and challenges for accounting education, particularly in developing social accounting competencies related to sustainability and social responsibility. This study aims to examine the effect of an IoT-based goat farming learning system on the development of social accounting competencies in vocational and applied accounting education. Using a quantitative explanatory research design, this study integrates a technology-enhanced learning approach supported by real-time data generated from IoT-enabled goat farming systems. Data were collected from students participating in IoT-based learning activities and analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results indicate that the IoT-based goat farming learning system has a positive and significant effect on social accounting competencies, including the ability to identify, measure, interpret, and report social and environmental impacts. The findings demonstrate that real-time livestock data provide an effective experiential learning environment that bridges the gap between abstract social accounting concepts and practical applications. This study contributes to accounting education literature by repositioning IoT-based livestock systems as pedagogical platforms rather than purely operational tools. The study also offers practical implications for educators, curriculum designers, and policymakers seeking to strengthen sustainability-oriented accounting education in digitally transformed agribusiness contexts.
AI-Based Digital Twin Development for Optimizing Hydrogen Production, Distribution, and Business Profitability Nicholas Renaldo; Jaswar Koto; M. Dalil; Dodi Sofyan Arief; Sulaiman Musa; Nindy Daviny; Cecilia Cecilia; Kristy Veronica
Journal of Applied Business and Technology Vol. 7 No. 1 (2026): Jounal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/s04p2v22

Abstract

The transition toward a low-carbon energy system has increased interest in green hydrogen as an energy carrier for renewable energy integration, industrial applications, and sustainable transportation. However, the economic competitiveness of hydrogen remains constrained by the complexity of coordinating renewable-energy availability, electrolyzer operation, hydrogen storage, distribution, market demand, and profitability. This study proposes an AI-Based Hydrogen Business Digital Twin (HBDT) to optimize hydrogen production, distribution, and business profitability through an integrated digital decision-making framework. The research employs a simulation-based development approach that combines Digital Twin technology, Artificial Intelligence, predictive analytics, multi-objective optimization, and techno-economic analysis. Several machine-learning models, including Random Forest, Support Vector Regression, XGBoost, Artificial Neural Network, and Long Short-Term Memory (LSTM), are evaluated for predictive performance. The simulation results indicate that LSTM provides the strongest performance, achieving an MAE of 0.041, RMSE of 0.068, and R2 of 0.981. Scenario analysis demonstrates that profitability increases from 12.5% under fixed production and distribution to 32.4% under the integrated AI, Digital Twin, and optimization scenario. The techno-economic simulation further indicates reductions in hydrogen production cost, levelized cost of hydrogen, and distribution costs, accompanied by improvements in renewable-energy utilization, revenue, ROI, and payback period. These findings demonstrate that the proposed HBDT can transform hydrogen management from a static and reactive process into a predictive, prescriptive, and potentially autonomous business ecosystem. The study contributes to the emerging concept of Hydrogen Business 4.0, in which technical operations and economic decisions are continuously optimized through AI and Digital Twin technologies.
Beyond Cold Storage and Smart Milk Bank as a Disruptive Supply Chain Innovation for Strengthening National Dairy Industry Resilience Nicholas Renaldo; Achmad Tavip Junaedi; Suhardjo Suhardjo; Azridjal Aziz; M. Dalil; Erpiani Siregar; Jahrizal Jahrizal; Umar Faruq; Jaswar Koto; Kristy Veronica
Journal of Applied Business and Technology Vol. 7 No. 2 (2026): Jounal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/b277se34

Abstract

The national dairy industry faces persistent challenges related to fluctuating milk supply, quality deterioration, limited traceability, and inefficiencies in conventional milk collection and storage systems. This study proposes the Smart Milk Bank (SMB) as a disruptive supply chain innovation that moves beyond the conventional function of cold storage by integrating rapid cooling, cold-chain management, real-time quality monitoring, digital traceability, inventory management, and an intermediary business model. An applied research and technology development approach is employed, involving system requirement analysis, prototype development, functional testing, industrial implementation, and performance evaluation. Data are obtained from milk quality measurements, sensor records, production and inventory data, operational observations, and stakeholder feedback. The proposed system is designed to transform the milk bank into an active supply-chain buffer capable of coordinating milk quality and volume according to industrial demand. Performance evaluation focuses on milk losses, quality consistency, supply stability, operating costs, traceability, and system reliability. The proposed targets include reducing damaged milk from approximately 10–15% to 6–8%, improving managed supply stability by 20–30%, and reducing operating costs by 15–25%. The study positions Smart Milk Bank as a systemic innovation in which technological integration and business-model innovation jointly strengthen dairy supply chain resilience. The findings provide a conceptual and practical foundation for developing a scalable, digitally enabled milk supply system that can support the competitiveness, sustainability, and resilience of the national dairy industry. 
Disrupting the Veterinary Value Chain through AI-Based Goat Health Management Achmad Tavip Junaedi; Nicholas Renaldo; Nyoto Nyoto; Erlin Erlin; Gustientiedina Gustientiedina; Yulvia Nora Marlim; Tito Suprayoga; Jahrizal Jahrizal; Umar Faruq; Kristy Veronica
Journal of Applied Business and Technology Vol. 7 No. 2 (2026): Jounal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/9x4hae67

Abstract

The digital transformation of livestock production is creating new opportunities to redesign conventional veterinary service delivery. However, veterinary services in goat farming remain constrained by limited personnel, geographic accessibility, delayed disease detection, and relatively high service costs. This study examines how artificial intelligence can disrupt the veterinary value chain through Kambing Light Vision, an AI-based goat health management platform that integrates Computer Vision, disease detection, prediction confidence, and AI-assisted veterinary care recommendations. An exploratory qualitative case study approach was employed by analyzing the technology development process, veterinary service workflow, stakeholder roles, commercialization pathways, and potential business value. The results indicate that AI can shift preliminary health assessment from a predominantly veterinarian-dependent process toward a digitally assisted and farmer-accessible service. This transformation can shorten information flows, reduce service and transaction bottlenecks, improve veterinary triage, and create new value propositions for farmers, veterinary clinics, cooperatives, and agribusiness organizations. The analysis further identifies subscription-based Software as a Service, technology licensing, and managed veterinary services as potential mechanisms for converting AI capabilities into scalable business value. The study argues that the disruptive potential of AI does not lie solely in disease-classification accuracy but in its ability to reconfigure the veterinary value chain and transform how veterinary services are accessed, delivered, and commercialized. Kambing Light Vision therefore represents a transition from AI as a diagnostic technology toward AI-enabled veterinary service infrastructure with potential implications for digital agriculture and sustainable livestock business.
Digital Transformation and Business Value Creation through Smart Patchouli Oil Distillation Achmad Tavip Junaedi; Nicholas Renaldo; Suhardjo Suhardjo; Bord Nandre Aprila; Yenny Desnelita; Wilda Susanti; Jahrizal Jahrizal; M. Dalil; Marice Br Hutahuruk; Kristy Veronica
Luxury: Landscape of Business Administration Vol. 4 No. 2 (2026): Luxury: Landscape of Business Administration
Publisher : First Ciera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61230/luxury.v4i2.156

Abstract

Digital transformation is increasingly important for improving the competitiveness and sustainability of agro-industrial enterprises, particularly in essential oil production where conventional distillation remains constrained by energy consumption, process variability, limited monitoring, and inconsistent product quality. This study examines the potential of Aroma Smart Distiller as a digital transformation innovation for creating business value in patchouli oil production. The system integrates precision steam distillation, Internet of Things (IoT), edge computing, artificial intelligence (AI), adaptive process control, and solar hybrid energy into an integrated smart production platform. An applied research and experimental development approach is used to evaluate operational efficiency, energy consumption, productivity, product quality, and commercialization potential. The proposed system targets a patchouli oil yield of 2.8–3.2%, a 20–30% increase in productivity, and a 30–40% reduction in energy consumption compared with conventional distillation. The integration of real-time monitoring and AI-based optimization also provides production data that can support managerial decision-making, quality control, energy management, and continuous process improvement. From a business perspective, the technology creates value through cost efficiency, productivity enhancement, quality differentiation, sustainability, and access to premium and export markets. The commercialization model further indicates opportunities through equipment sales, intellectual property, licensing, and technology scale-up. The study concludes that smart distillation can function not only as a production technology but also as a strategic digital transformation mechanism for creating sustainable business value and strengthening the competitiveness of small and medium-sized enterprises in the essential oil industry.
Co-Authors Achmad Tavip Junaedi Amries Rusli Tanjung Azridjal Aziz Bord Nandre Aprila Cecilia Cecilia Desnelita, Yenny Dodi Sofyan Arief Erlin Erlin Erpiani Siregar Evelyn Wijaya Fifi Puspita Gatot Wijayanto Gustientiedina Harry Patuan Panjaitan Intan Purnama Jahrizal Jaswar Koto M Dalil M. Dalil Marice Br Hutahuruk Marice Br Hutahuruk Marlim, Yulvia Nora Nabila Wahid Nicholas Renaldo Nindy Daviny Nyoto Onny Setyawan Rahma Widi Rangga Rahmadian Yuliendi Rebecca La Volla Nyoto Rizaldi Putra Sri Indrastuti Suhardjo Suhardjo Sulaiman Musa Sulaiman Musa Tito Suprayoga Umar Faruq Umar Faruq Wahyu Joni Kurniawan Wilda Susanti