cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
NICHOLAS RENALDO
Contact Email
nicholasrenaldo@lecturer.pelitaindonesia.ac.id
Phone
+62761 24418
Journal Mail Official
jabt@pelitaindonesia.ac.id
Editorial Address
Institut Bisnis dan Teknologi Pelita Indonesia Jend. Ahmad Yani Street No. 78-88, Pekanbaru, Riau, Indonesia 28127
Location
Kota pekanbaru,
Riau
INDONESIA
Journal of Applied Business and Technology
Published by INSTITUT BISNIS DAN TEKNOLOGI PELITA INDONESIA
ISSN : 27225372     EISSN : 27225380     DOI : https://doi.org/10.35145/jabt
Core Subject : Economy, Science,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
JABT (Journal of Applied Business and Technology) is a media for exploration and discussion about Business Management and Technological problems arised in the society. It includes scientific articles in the form of research results, theory application, analytical studies, and literature studies on both areas. JABT also accumulates the literature reviews and critiques in improving theories and researches and offer contributions in delevoping educational methodology in the area of Business Management and Technology.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 159 Documents
 12   13   14   15   16 
The Role of Spiritual Intelligence Moderation in Improving Organizational Commitment and Employee Performance at Ministry of Religion Regional Office Poniman Poniman; Evelyn Wijaya; Harry Patuan Panjaitan
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: 10.35145/5tad1f87

Abstract

In carrying out government and development activities, the position and role of civil servants are crucial. Civil servants are elements of the state apparatus that carry out elements of government and development in an effort to achieve organization goals. This research aims to analyze impact on islamic leadership and organization culture to organizational commitment and employee performance with spiritual intelligence as moderating variable. Research population were all employees at Ministry of Religion Regional Office of Riau Province with total sample as 150 respondents with cencus method. Data analysis used Structural Equation Modeling (SEM) with SMARTPLS 4.0.0. Research result show that organization culture has impact on organizational commitment and employee performance, islamic leadership has impact on employee performance but has not impact on organizational commitment. Organizational commitment has not impact on employee performance. Spiritual intelligence strengthen impact on organization culture to organizational commitment and employee performance. Spiritual intelligence weaken impact on islamic leadership to organizational commitment and employee performance. To maximize individual potential and enhance overall organizational results, spiritual intelligence development should be incorporated into training and culture.
Precision Multi-Forage Nutrition as a Driver of Sustainable Goat Agribusiness Performance Nicholas Renaldo; Jahrizal Jahrizal; Achmad Tavip Junaedi; Suhardjo Suhardjo; Onny Setyawan; Sulaiman Musa; Cecilia Cecilia
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/s2a28145

Abstract

Feed cost remains the largest expenditure in goat farming enterprises and significantly influences profitability, competitiveness, and long-term sustainability. Despite advances in precision livestock farming, limited studies have examined precision nutrition from an agribusiness perspective, particularly in tropical goat production systems. This study aims to analyze the role of Precision Multi-Forage Nutrition (PMFN) as a driver of sustainable goat agribusiness performance through the strategic integration of seven functional forage crops: Bonanza maize (Zea mays), Sweet Lady maize (Zea mays), Indigofera zollingeriana, Anaphalis javanica, Medicago sativa, Pakchong grass (Pennisetum purpureum × Pennisetum americanum), and Odot grass (Pennisetum purpureum cv. Mott). Using a descriptive case study approach combined with techno-economic and agribusiness feasibility analyses, the study evaluates the nutritional, operational, and economic contributions of diversified forage resources within integrated goat farming systems. The findings indicate that the PMFN framework enhances feed security, improves resource utilization efficiency, reduces dependence on external feed markets, and strengthens business resilience. The integration of seven complementary forage species creates a balanced nutritional ecosystem that supports productivity while simultaneously optimizing feed costs and improving profitability. Guided by the Resource-Based View (RBV), the study demonstrates that diversified forage resources can function as valuable, rare, inimitable, and non-substitutable strategic assets that contribute to sustainable competitive advantage. Furthermore, the study introduces the concept of Forage-Based Competitive Advantage (FBCA), which positions forage diversity and precision nutrition as strategic drivers of agribusiness performance rather than merely production inputs. The results suggest that Precision Multi-Forage Nutrition represents a transformative agribusiness innovation capable of enhancing economic sustainability, operational resilience, and long-term competitiveness in goat farming enterprises. These findings provide theoretical contributions to agribusiness strategy literature and practical implications for farmers, investors, and policymakers seeking sustainable livestock development models.
Building Student Entrepreneurship Spirit Through Innovation Strategy Muliadi Rizki; Eddy Noviana; Masyitha Ramadhani; Rahma Widi; Wilda Susanti
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/r50t3308

Abstract

This study consists of one variable, namely the Entrepreneurial Strategy of Community Education Students of FKIP Universitas Riau. The concept of the entrepreneurial strategy of community education students of FKIP Universitas Riau in question is an action plan prepared by entrepreneurs to achieve their business goals. This strategy includes strategic decisions and steps to develop, create, and grow a business, which is illustrated by: 1) Plan, 2) Pattern, 3) Position, and 4) Perspective. The subjects of this study amounted to 4 people who will be used as research information. The purpose of this research is to find out data and information about the Entrepreneurial Strategy of FKIP Students at Universitas Riau. The determination of the research subject is based on the consideration that the informant can provide the data and information needed in the research.
Comparison of Support Vector Machine Kernel Performance In Sentiment Analysis of The Free Lunch Program Emanuel Zega; Erlin
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/gtv1sr05

Abstract

The Free Lunch Program is a government policy that has generated various opinions on social media, ranging from support to criticism regarding its implementation. This study aims to analyze public sentiment before and after the implementation of the Free Lunch Program using the Support Vector Machine (SVM) algorithm and to compare the performance of several kernels, namely Linear, Polynomial, RBF, and Sigmoid. The data were collected from the X (Twitter) platform and classified into three sentiment categories: positive, negative, and neutral. The experimental results show that the RBF kernel achieved the best performance, with an accuracy of 97.04% on pre-implementation data and 96.32% on post-implementation data. Moreover, the sentiment analysis results indicate that the proportion of negative sentiment increased after the program’s implementation, rising from 54.5% to 57.7%. These findings suggest that the RBF kernel is the most effective in classifying public opinions regarding the Free Lunch Program policy with a high level of accuracy, while also illustrating that public perception tends to be more critical after the program was implemented.
A Web-Based Information System for Detainee Data Management at Badan Narkotika Nasional (BNN) in Jambi Province Zikri Saputra; Sukma Puspitorini; Teuku Djauhari
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/w9vf6r36

Abstract

This research is based on the problem of manual recording which is at risk of data loss and misuse. This research aims to develop a web-based information system that facilitates the management of prisoner data, detainees, and evidence at the National Narcotics Agency (BNN) of Jambi Province. By applying the Research and Development (R&D) method and the Waterfall approach. The features implemented include input of prisoner data, prisoner data management, and recording of evidence. The test results show that the system works well and makes it easier for officers to record and manage data. The system also provides output in the form of reports which will later make it easier for officers to report starting from prisoner data, detainee data and confiscated evidence data. The system is built into a website-based application. It is hoped that this system will not only replace manual methods, but also make a real contribution in supporting BNN's task in eradicating narcotics abuse. The research findings can be a reference for the development of information systems in other agencies with similar needs. Keywords: Human Resource Digitalization Generative AI Talent Management Performance Monitoring Executive Information Systems.
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. 
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.

Page 16 of 16 | Total Record : 159

 12   13   14   15   16 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 7 No. 2 (2026): Jounal of Applied Business and Technology Vol. 7 No. 1 (2026): Jounal of Applied Business and Technology Vol. 6 No. 3 (2025): Journal of Applied Business and Technology Vol. 6 No. 2 (2025): Journal of Applied Business and Technology Vol. 6 No. 1 (2025): Journal of Applied Business and Technology Vol. 5 No. 3 (2024): Journal of Applied Business and Technology Vol. 5 No. 2 (2024): Journal of Applied Business and Technology Vol. 5 No. 1 (2024): Journal of Applied Business and Technology Vol. 4 No. 3 (2023): Journal of Applied Business and Technology Vol. 4 No. 2 (2023): Journal of Applied Business and Technology Vol. 4 No. 1 (2023): Journal of Applied Business and Technology Vol. 3 No. 3 (2022): Journal of Applied Business and Technology Vol. 3 No. 2 (2022): Journal of Applied Business and Technology Vol. 3 No. 1 (2022): Journal of Applied Business and Technology Vol. 2 No. 3 (2021): Journal of Applied Business and Technology Vol. 2 No. 2 (2021): Journal of Applied Business and Technology Vol. 2 No. 1 (2021): Journal of Applied Business and Technology Vol. 1 No. 3 (2020): Journal of Applied Business and Technology Vol. 1 No. 2 (2020): Journal of Applied Business and Technology Vol. 1 No. 1 (2020): Journal of Applied Business and Technology More Issue