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All Journal Journal of Applied Business and Technology Luxury: Landscape of Business Administration
M. Dalil
Universitas Riau, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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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.
Digital Transformation of Goat Milk Supply Chains through an Integrated Smart Cold-Chain Logistics System Nyoto Nyoto; Nicholas Renaldo; Jahrizal Jahrizal; Azridjal Aziz; M. Dalil; Achmad Tavip Junaedi; Yusrizal Yusrizal; Alyauma Hajjah; Sulaiman Musa; Cecilia Cecilia
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/re8a7652

Abstract

The rapid digital transformation of agribusiness has created significant opportunities to improve supply chain efficiency, product quality, and operational sustainability through the integration of smart technologies. However, goat milk supply chains continue to face challenges associated with short product shelf life, inadequate cold-chain infrastructure, limited distribution visibility, and high logistics costs, particularly among small and medium-sized enterprises (SMEs). This study aims to develop and evaluate an Integrated Smart Cold-Chain Goat Milk Logistics System (SCGLMS) as a digital transformation model for goat milk supply chains. A Design Science Research (DSR) methodology was employed, consisting of problem identification, system design, prototype development, pilot implementation, and system evaluation. The proposed SCGLMS integrates four interconnected layers: smart milk processing, intelligent packaging, IoT-enabled cold-chain logistics, and a cloud-based digital management platform that provides real-time monitoring, digital traceability, and logistics analytics. The findings demonstrate that the integrated system significantly improves supply chain visibility, operational coordination, and decision-making by enabling continuous monitoring of temperature, humidity, shipment status, and product quality throughout distribution. The system also enhances logistics efficiency, minimizes product spoilage, extends market accessibility, and strengthens customer confidence through improved transparency and traceability. This study contributes to the literature on digital supply chain management by proposing a comprehensive technological framework specifically designed for goat milk logistics. Furthermore, it provides practical guidance for SMEs, agribusiness practitioners, and policymakers seeking to accelerate digital transformation and sustainable supply chain development within the dairy industry.
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. 
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.
From Waste to Assets through Value Creation Strategies in Goat Farming Nicholas Renaldo; Achmad Tavip Junaedi; Wilda Susanti; Jahrizal Jahrizal; M. Dalil; Kristy Veronica; Marice Br Hutahuruk; Sulaiman Musa; Jaswar Koto; Cecilia Cecilia
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.v4i2.159

Abstract

This study examines the transformation of livestock waste into economic and environmental value through innovation in goat farming. The study applies a qualitative case study approach using observation, interviews, and documentation of a Smart Composting System. The system utilizes leftover fermented corn-stalk and leaf silage, goat manure, horse manure, EM4, and brown sugar, supported by Internet of Things (IoT)-based monitoring of temperature, moisture, and NPK. The findings indicate that the innovation enables organic waste to be transformed into compost while generating operational data that can support more effective management decisions. The integration of environmental accounting further enables the identification of processing costs, potential economic value, and environmental benefits. The study demonstrates that waste management can be repositioned from a cost-oriented activity into a value creation strategy through the integration of resource recovery, digital technology, and environmental-economic measurement. The proposed approach provides a practical foundation for developing circular and sustainable business practices in goat farming.
Co-Authors Achmad Tavip Junaedi Alyauma Hajjah Azridjal Aziz Bord Nandre Aprila Cecilia Cecilia Desnelita, Yenny Dodi Sofyan Arief Erpiani Siregar Jahrizal Jaswar Koto Kristy Veronica Marice Br Hutahuruk Marice Br Hutahuruk Nicholas Renaldo Nindy Daviny Nyoto Suhardjo Suhardjo Sulaiman Musa Umar Faruq Wilda Susanti Yusrizal Yusrizal