International Journal of Multidisciplinary Research and Creative Innovation Ideas
The International Journal of Multidisciplinary Research and Creative Innovation Ideas (The MIR) is a scholarly publication dedicated to fostering high-quality research across diverse academic disciplines. This journal serves as a platform for: Multidisciplinary research in pure sciences and various educational fields. Studies on the development of educational applications, including comprehensive analysis and evaluation. Exploration of creative and innovative ideas that contribute to advancements in research and practical implementations. The MIR welcomes original research articles, case studies, and review papers that align with its scope, aiming to bridge the gap between theoretical knowledge and real-world applications.
Economic Resilience Of Street Vendors In The Era Of Rupiah Depreciation: A Theoretical Conceptual Study Of Informal Economics
This study examines the economic resilience of Pedagang Kaki Lima (PKL) or street vendors during rupiah depreciation in Indonesia's informal economy. The research aims to explain how depreciation pressure affects PKL resilience and identify the mechanisms through which this relationship operates. Using a mixed-methods approach, the study combines quantitative analysis (120 PKL respondents: 60 from UNNES Semarang, 60 from Mojokerto) with qualitative data (12 interviews, participant observation, document analysis, and one Focus Group Discussion). Quantitative results show that rupiah depreciation pressure does not directly reduce PKL economic resilience (β = -0.08, p = 0.342), but instead influences resilience through three intervening variables: informal economy adaptation (r = 0.42, p < 0.001), microeconomic adjustment (r = 0.38, p < 0.001), and social capital (r = 0.35, p < 0.001). Social capital is the strongest predictor of resilience (β = 0.38, p < 0.001), followed by informal economy adaptation (β = 0.31, p < 0.001) and microeconomic adjustment (β = 0.27, p = 0.002). The regression model explains 48% of variance in PKL resilience (R² = 0.48, p < 0.001). Qualitative findings reveal that PKL respond to depreciation through price adjustments, early purchasing, product diversification, and collective strategies such as rotating savings groups and bulk purchasing coordination. PKL in UNNES Semarang demonstrate significantly higher resilience (M = 3.58) than Mojokerto PKL (M = 3.26, p = 0.002) due to better market conditions and organized vendor structures. The study concludes that PKL resilience during currency depreciation is a multi-dimensional process shaped by adaptive behaviors and strong social capital networks. These findings support social capital theory and extend informal economy theory by demonstrating that group-based resilience mechanisms are more critical than individual strategies in informal settings.
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The Role Of Entrepreneurial Leadership In Driving Green Management And Innovation Performance Among Creative Industry SMEs in Bali
This study examines the role of entrepreneurial leadership and green management in driving innovation performance among creative industry SMEs in Bali. Increasing environmental pressures and market uncertainty require SMEs to remain innovative while adopting environmentally responsible management practices. Drawing on Dynamic Capabilities Theory, this study conceptualizes innovation performance as an outcome of internal managerial capabilities orchestrated by entrepreneurial leadership and supported by green management practices. A quantitative explanatory research design was employed using survey data collected from 86 owners or managers of creative industry SMEs in Bali. Data were analyzed using multiple linear regression to test the direct effects of entrepreneurial leadership and green management on innovation performance. The results indicate that both entrepreneurial leadership and green management have a positive and significant effect on innovation performance. However, entrepreneurial leadership demonstrates a more dominant influence, while the contribution of green management is relatively weak, suggesting that environmental practices in SMEs are still largely operational rather than strategically oriented toward innovation. These findings highlight the central role of entrepreneurial leadership in transforming managerial capabilities into innovation outcomes and suggest that green management requires deeper strategic integration to enhance innovation performance in SMEs effectively. This study contributes to the literature by providing empirical evidence from a developing-country context and offers practical implications for strengthening innovation-oriented and sustainable management in creative industry SMEs.
The Influence of Sustainable Tourism Practices on Destination Loyalty through Tourist Satisfaction as a Mediating Variable
Sustainable tourism practices have become increasingly important in maintaining environmental integrity and enhancing tourist experiences. However, their role in fostering destination loyalty remains unclear, particularly through the mechanism of tourist satisfaction. This study aims to examine the influence of sustainable tourism practices on destination loyalty, with tourist satisfaction acting as a mediating variable. This research employs a quantitative approach using a Structural Equation Modeling (SEM) design with the Partial Least Squares (PLS-SEM) technique. Data were collected from 250 domestic tourists through a structured questionnaire. The sampling technique applied was purposive sampling, targeting tourists who had experienced destinations implementing sustainable tourism practices. Respondents were selected based on their travel experience and familiarity with sustainability-related initiatives at the destination. The results indicate that sustainable tourism practices have a significant positive effect on tourist satisfaction. Tourist satisfaction also significantly influences destination loyalty, confirming its role as a key determinant in tourists’ revisit intentions and recommendations. Furthermore, the mediation analysis reveals that tourist satisfaction partially mediates the relationship between sustainable tourism practices and destination loyalty. In conclusion, sustainable tourism practices play a crucial role in enhancing tourist satisfaction, which in turn strengthens destination loyalty. The findings imply that destination managers should prioritize sustainability initiatives not only for environmental benefits but also as a strategic tool to improve tourist satisfaction and long-term loyalty.
The Impact of Augmented Reality Experiences on Traveler Engagement, Satisfaction, and Intent to Visit
This study analyzes the impact of Augmented Reality (AR) experiences on tourist engagement, satisfaction, and intention to visit using an integrated causal model in Thailand-Indonesia cultural destinations. The PRISMA Systematic Literature Review (SLR) from Scopus (47 studies) was combined with empirical validation through the TAM/UTAUT2 questionnaire (n=250 respondents of ISIC RMUTK Thailand). The SEM-AMOS analysis tested 5 Research Questions with superior goodness-of-fit (CFI=0.96, RMSEA=0.05). AR interactivity predicted engagement (β=0.693, p<0.001), which mediated satisfaction (R²=0.563) and intent to visit (a total effect of 89.4% variation). The complete model is 79.5% superior to the previous partial study (Putri et al., 2025). The dominance of engagement as a mediator and the accessibility gap (10.6%) underscore the urgency of a digital-conventional hybrid framework for optimal tourism ROI (Sari & Pratama, 2024). The AR design framework is recommended for destination managers, potentially increasing visitor intent by up to 75% through QR-code integration and digital literacy. This study enriches the Technology Acceptance Model with a specific tourism dimension, providing a standard SEM methodology for future AR studies.
Digital Accessibility for People with Visual Impairments: Challenges, Opportunities, and Inclusive Technology Solutions
This study discusses the importance of digital access for people with visual impairments (visually impaired) in the midst of the rapid development of information technology. Although technology has the potential to help everyone, there are still many digital applications that are not easy for a blind person to use. The development of information and communication technology has provided various conveniences in accessing information digitally. However, not all individuals can enjoy such access equally, especially the visually impaired. Digital accessibility is an important aspect in ensuring that technology can be used by everyone without exception. This research aims to analyze the importance of digital literacy and the application of digital accessibility for a blind person in accessing technology-based information and services. The research method used is descriptive qualitative with literature studies from various scientific sources related to digital literacy and technological accessibility. The results of the study show that the application of Web Content Accessibility Guidelines (WCAG) and the use of tools such as screen readers or text-to-speech can help blind users access information on the internet. The application of a design that is easily accessible to everyone is not only a technical matter, but also a form of fulfilling everyone's right to information. Therefore, cooperation between the government, technology developers, and the community is needed to increase inclusive digital accessibility.
Web Content Accessibility Guidelines (WCAG)
Barriers and Drivers of Digital Transformation among Tourism MSMEs. A Qualitative Exploration of Challenges, Adaptation Strategies, and Digital Readiness
This research is based on the low level of digital transformation of tourism MSMEs, even though the adoption of digital technology is considered a key factor in competitiveness in the digital era. This study aims to analyze the influence of barriers to digital transformation in tourism, adaptation strategies to digital transformation, and digital readiness on the digital performance of tourism MSMEs through a quantitative approach. The research method combines a PRISMA-based Systematic Literature Review (SLR) adapted to identify relevant variables and indicators from Scopus-indexed journals (2021–2026), followed by quantitative research on a causal comparative design using questionnaires on tourism MSME actors around campus in Bali and tourists. The data was analyzed with Structural Equation Modeling (SEM) through SmartPLS 4 to test the relationship between barriers, adaptation strategies, digital transformation, digital readiness, and digital performance of tourism MSMEs. The results show that adaptation strategies play a strong role as a driver of digital transformation, while barriers have a negative impact, and digital readiness is a significant mediator in the relationship between digital transformation and the digital performance of tourism MSMEs. The main conclusion of this study is that the development of digital readiness and effective adaptation strategies is essential to increase the positive impact of digital transformation on tourism MSMEs. Contribution in the field lies in strengthening the quantitative basis for training program design, digital support policies, and strategies to strengthen the capacity of tourism MSMEs in the face of the digital transformation of the tourism sector
barriers to digital transformation in tourism
adaptation strategies to digital transformation
The Influence of Social Media Marketing on Customer Engagement and Purchase Intention in Culinary Tourism: A Systematic Literature Review and Qualitative Synthesis from Bali Agribusiness Perspective
Social media has become a dominant channel in promoting culinary destinations and gastronomy-based tourism experiences, yet evidence on how social media marketing drives customer engagement and purchase intention in culinary tourism is still fragmented and mostly context-specific. Most prior studies are quantitative and platform- or brand-centric, with limited integration between tourism, gastronomy, and agribusiness perspectives. This study employed a mixed qualitative design combining a Systematic Literature Review (SLR) of Scopus-indexed articles and a qualitative synthesis using thematic analysis. The SLR followed PRISMA steps—identification, screening, eligibility, and inclusion—using keywords related to social media marketing, customer engagement, purchase intention, and culinary or gastronomy tourism. Additional contextual qualitative data were obtained through semi-structured online interviews with five culinary tourism stakeholders in Bali (restaurant owners, tour operators, and digital marketers), selected by purposive sampling.journal.poltekparmakassar. The SLR identified that social media marketing positively influences customer engagement and purchase intention, with customer engagement often acting as a mediating variable between social media activities and purchasing behavior. In the culinary and gastronomy context, visual content quality, electronic word of mouth (e WOM), trust, and perceived authenticity emerged as dominant drivers of intention to visit and buy. Qualitative insights from Bali stakeholders emphasized the strategic role of Instagram and TikTok reels, user-generated content, and collaboration with food influencers to trigger trial, repeat visits, and cross-selling of local agricultural products. The synthesis shows that social media marketing in culinary tourism operates through four core mechanisms: (1) information sharing, (2) social interaction and community building, (3) e WOM and trust formation, and (4) experiential storytelling that enhances perceived destination value. However, most existing studies do not explicitly connect these mechanisms to upstream agribusiness value chains, local farmers, and rural gastronomic development. exsys.This article offers a high novelty contribution by integrating culinary tourism, social media marketing, and agribusiness perspectives through an SLR and qualitative thematic analysis anchored in the Bali context. It proposes an integrated conceptual model linking social media marketing, customer engagement, and purchase intention in culinary tourism, with specific implications for agribusiness-based product differentiation and destination branding. Future empirical research from Prodi Agribisnis, Fakultas Pertanian dan Bisnis, Universitas Mahasaraswati Denpasar, is encouraged to test this model using mixed methods designs in Bali’s culinary tourism clusters.
The Hidden Human Resources: The Role of Gastronomy Experience in Destination Branding and Tourist Loyalty
This research is motivated by the need to understand the factors that influence tourists' intention to adopt augmented reality (AR) at geosite destinations, particularly in the context of Batur UNESCO Global Geopark. The purpose of this study is to analyze the influence of perceived usefulness, perceived ease of use, perceived enjoyment, perceived interactivity, and destination branding perception on behavioral intention to adopt AR through attitude toward AR or tourist engagement as a mediating variable. The research method uses a systematic literature review approach to develop a conceptual framework and a quantitative survey to test the empirical model on tourists at Batur Geosite and related respondents in Bali. Data were collected using a Likert-scale questionnaire from tourists and potential visitors, then analyzed using Structural Equation Modeling to test the direct and indirect relationships between variables. The results show that perceptions of usefulness, ease of use, enjoyment, interactivity, and destination image contribute to tourists' intention to adopt AR, primarily through positive attitudes and tourist engagement. This research contributes to the development of tourism technology adoption and destination branding literature by providing an empirical model that can be used to design Human Resource strategies for more effective use of AR in geopark tourist destinations
Digital Adoption, Business Innovation, and Competitive Advantage of Tourism MSMEs. Integrating Quantitative Evidence and Qualitative Insights in a Mixed Methods Study
Digital transformation is an important factor for tourism micro, small, and medium enterprises (MSMEs) in increasing competitiveness in the midst of rapid market changes. This study aims to analyze the influence of digital adoption and ICT capability on competitive advantage through organizational capability in tourism MSMEs around Mahasaraswati University, Denpasar, Bali. This study uses a convergent mixed-method approach, with the initial stage of a systematic literature review (SLR) to identify constructs, indicators, and intervariable relationships from reputable journals, followed by quantitative research through a questionnaire survey of tourism MSMEs. Data were analyzed using SEM to test the direct and indirect influence between variables, as well as to evaluate the mediating role of organizational capability. The results of the study show that digital adoption and ICT capability contribute to strengthening organizational capability and competitive advantage. This research provides practical contributions for MSMEs, tourism actors, and policymakers in designing more effective and sustainable digitalization strategies
The Effect of Digital Marketing Capability and Business Innovation on MSMEs Performance in the Tourism Sector. Evidence from Small Tourism Enterprises Using
Digital marketing capability and online marketing capability are critical factors determining the business sustainability of MSMEs in the post-pandemic tourism sector, but there has been no research that has comprehensively tested the role of business innovation mediation. This study aims to analyze the influence of digital marketing capability and online marketing capability on the performance of MSMEs with business innovation as a mediating variable in tourism MSMEs. The method used is Sequential Literature Review (SLR) based on PRISMA 2020 with a search of 950 articles in the SCOPUS database for the 2022-2025 period using 5 key keywords. The qualitative stage was continued with quantitative research using Structural Equation Modeling (SEM-PLS) on 120 tourism MSME respondents in STIMI Handayani and its surroundings in Surabaya. The research instrument used a closed questionnaire on a Likert scale of 1-5 with 18 indicators that have been validated from the literature synthesis. Data were analyzed using SmartPLS 4 to test 5 direct and indirect relationship hypotheses. The results showed that Digital Marketing Capability (β=0.328, p=0.020) and Online Marketing Capability (β=0.209, p=0.013) had a significant positive effect on MSMEs Performance with Business Innovation as a significant partial mediation (β=0.125, p=0.022; R²=0.501, Q²=0.468). This research provides empirical guidance for tourism MSMEs to invest resources in digital capabilities and business innovation to improve operational performance, market expansion, and profitability in a sustainable manner.
Virtual Reality-Based Promotion and Its Effect on Destination Image and Travel Intention
This research is based on the increasing use of virtual reality in tourism promotion to shape destination image and encourage travel intention. The purpose of this study is to analyze the influence of virtual reality-based promotion on destination image and travel intention with immersion as a mediator. The research method uses a quantitative approach with a causal design, supported by a systematic literature review to compile conceptual models and variable indicators. Data was collected through a Likert scale questionnaire from respondents who had experienced destination VR promotions, and then analyzed using SEM-PLS to test the direct and indirect relationships between variables. The results of the study show that VR-based promotion has a positive effect on destination image and travel intention, and immersion strengthens this influence as a significant mediation channel. This research provides a practical contribution for destination managers in designing digital promotions that are more immersive, interactive, and effective to increase tourist interest in visits.
This study analyzes the impact of Augmented Reality (AR) experiences on tourist engagement, satisfaction, and intention to visit using an integrated causal model in Thailand-Indonesia cultural destinations. The PRISMA Systematic Literature Review (SLR) from Scopus (47 studies) was combined with empirical validation through the TAM/UTAUT2 questionnaire (n=250 respondents of ISIC RMUTK Thailand). The SEM-AMOS analysis tested 5 Research Questions with superior goodness-of-fit (CFI=0.96, RMSEA=0.05). AR interactivity predicted engagement (β=0.693, p<0.001), which mediated satisfaction (R²=0.563) and intent to visit (a total effect of 89.4% variation). The complete model is 79.5% superior to the previous partial study (Putri et al., 2025). The dominance of engagement as a mediator and the accessibility gap (10.6%) underscore the urgency of a digital-conventional hybrid framework for optimal tourism ROI (Sari & Pratama, 2024). The AR design framework is recommended for destination managers, potentially increasing visitor intent by up to 75% through QR-code integration and digital literacy. This study enriches the Technology Acceptance Model with a specific tourism dimension, providing a standard SEM methodology for future AR studies
Crisis Management Strategy and Tourism Resilience. A Mixed Methods Study on Stakeholder Adaptation and Recovery in Tourism Destinations
This research is motivated by the dependence of tourism destinations on effective crisis management to build destination resilience and accelerate post-crisis recovery. The purpose of this study is to examine the direct and indirect effects of crisis management on destination resilience through stakeholder adaptation using a sequential mixed-methods design. The research methodology combines protocol-based SLR to formulate a framework of variables and indicators, followed by a questionnaire survey of students of tourism universities in Bali and tourists who have visited major destinations in Bali, with samples selected purposively. Quantitative data were analyzed using Structural Equation Modeling (SEM) to examine the direct and indirect relationships between crisis management (independent variable), stakeholder adaptation (mediating variable), and destination resilience (dependent variable). The main conclusion of this study shows that crisis management has a positive and significant effect on destination resilience, largely through the mediating effect of stakeholder adaptation. Therefore, active adaptation by communities and businesses is key to developing resilient tourism destinations. Keywords: crisis management, destination resilience, stakeholder adaptation.
Sustainable Gastronomy Practices and Their Impact on Tourist Experience and Behavioral IntentionA Quantitative Investigation of Eco-Friendly Culinary Tourism
Sustainable culinary tourism is increasingly important amidst global environmental pressures, yet quantitative research on the impact of sustainable gastronomy practices on tourist experience and behavioral intention in the Indonesian context is still lacking. This study aims to examine the influence of sustainable gastronomy practices on tourist experience and behavioral intention in eco-friendly culinary tourism in Bali/Surabaya. The study used a mixed-method approach through a Systematic Literature Review (SLR) and a quantitative survey using SEM-PLS. The results show that sustainable gastronomy practices have a significant influence on tourist experience and behavioral intention. These findings provide theoretical contributions to the development of SDGs in the context of sustainable gastronomy and provide practical implications for culinary destination managers
The Effect of Food Quality, Authenticity, and Service Quality on Tourist Satisfaction and Loyalty in Culinary Tourism: A Quantitative Study of Experiential Value in Gastronomy Destinations
This study analyzes the influence of meal quality, restaurant quality, and food perceived quality on the satisfaction and loyalty of culinary tourists, where previous studies have shown inconsistent findings regarding the mediation of experiential value. The main objective is to quantitatively test the influence of meal quality and restaurant quality on tourist satisfaction and loyalty, with food perceived quality and experiential value as mediators using the SEM-PLS model. The study uses a mixed-method approach: a systematic literature review (SLR) following the PRISMA and Kitchenham protocols to formulate hypotheses from Scopus literature (2010-2026), followed by a quantitative survey of 320 respondents visiting culinary visitors around Mahasaraswati University, Denpasar. Data were collected via a Likert 1-5 questionnaire adapting a tested scale (e.g., Namkung & Jang 2007 for meal quality, SERVQUAL for restaurant quality), with purposive sampling and online/face-to-face distribution. Analysis was conducted using PLS-SEM to test validity, reliability, causal pathways, mediation (bootstrapping), and moderation, ensuring statistical assumptions were met. Meal quality and restaurant quality significantly increase experiential value, satisfaction, and tourist loyalty through the mediation of food perceived quality and experiential value, with restaurant quality moderating the effect of meal quality. The main contribution is a new integrated model that combines the constructs of food-restaurant quality with experiential value mediation, filling the gap in sectoral studies and supporting the managerial strategy of gastronomic destinations in Indonesia
AI-Enhanced Vocational School Management Framework: A Systematic Review and Novel Implementation Model for Indonesian SMK Daily Operations.
The integration of artificial intelligence (AI) in vocational school management presents transformative opportunities for enhancing daily operational efficiency, particularly in resource-constrained contexts. This systematic literature review examines AI applications in educational management and proposes a novel AI-Enhanced Vocational School Management Framework (AI-VSMF) specifically designed for Indonesian Sekolah Menengah Kejuruan (SMK) daily operations. Through a comprehensive analysis of 129 high-quality Scopus-indexed publications (2020-2026), we identified key AI technologies and management applications across administrative automation, student performance monitoring, resource optimization, and decision support systems. The proposed AI-VSMF framework integrates four core modules: (1) Intelligent Administrative Operations, (2) Smart Student Management, (3) Adaptive Learning Analytics, and (4) Resource Optimization Engine. Contextualized for SMK Bondowoso, Indonesia, the framework emphasizes cost-effective, scalable solutions suitable for resource-limited vocational schools. This study contributes a practical implementation roadmap that addresses infrastructure constraints, technical capacity, and cultural adaptation needs specific to Indonesian vocational education contexts. The framework offers actionable pathways for SMK administrators to leverage AI technologies for improving operational efficiency, student outcomes, and institutional competitiveness in the evolving digital education landscape.
Navigating AI Integration in South African Higher Education: A Systematic Review of Tools, Challenges, and Opportunities.
This systematic literature review explores the adoption, application, and impact of artificial intelligence (AI) tools in South African higher education institutions, with emphasis on everyday teaching and learning practices. Through qualitative analysis of 30 Scopus-indexed studies published between 2020 and 2025, this review identifies key AI applications including generative AI assistants (ChatGPT), adaptive learning systems, automated assessment tools, and AI-powered teaching assistants. The novelty of this study lies in its focused examination of the South African context, revealing unique challenges including infrastructure constraints, digital inequality, policy gaps, and academic integrity concerns, alongside innovative local solutions such as mobile-first platforms and bilingual AI assistants. Thematic analysis uncovers mixed perceptions among students and educators: while AI enhances engagement, personalization, and scalable feedback, concerns persist regarding equity, preparedness, and ethical governance. This review contributes practical recommendations for South African universities, including context-aware tool adoption, inclusive policy development, assessment redesign, and regional collaboration frameworks. The findings advance understanding of AI integration in resource-constrained higher education environments and provide actionable insights for institutions like Durban University of Technology seeking to harness AI’s transformative potential while addressing contextual barriers
Artificial Intelligence Integration in Thai Education: A Systematic Literature Review of Everyday Learning Applications
This systematic literature review examines the integration of artificial intelligence (AI) in everyday educational practices within the Thai educational context. Through a comprehensive analysis of 30 peer-reviewed studies published between 2020 and 2026, this review identifies key AI applications, adoption patterns, implementation challenges, and opportunities specific to Thailand’s educational landscape. The findings reveal that generative AI tools, intelligent chatbots, and adaptive learning systems are increasingly integrated across educational levels, with higher education showing more advanced adoption than K-12 settings. Key challenges include infrastructure limitations, digital literacy gaps, language barriers for non-native English speakers, and concerns about academic integrity and over-reliance on technology. The novelty of this review lies in its focused examination of AI in everyday Thai educational practices, revealing unique cultural and contextual factors that influence AI adoption, including the tension between technological innovation and traditional pedagogical values. This study provides evidence-based recommendations for policymakers, educators, and institutions to enhance AI integration while preserving the essential human elements of teaching and learning in the Thai context
Smart Agriculture In Bali: A Systematic Review of Artificial Intelligence Applications for Tropical Farming
This systematic literature review examines artificial intelligence (AI) applications in agriculture with specific implications for Bali’s unique agricultural landscape. Through a comprehensive analysis of 20 Scopus-indexed articles (2019-2026), this study identifies key AI technologies, applications, and adoption barriers relevant to Balinese farming contexts. The review reveals that AI-driven solutions—including deep learning for disease detection (achieving 92-99% accuracy), IoT-based precision irrigation (reducing water use by 30%), and machine learning recommendation systems (99% accuracy)—offer transformative potential for Bali’s rice-dominated agriculture. However, adoption faces significant barriers including infrastructure limitations, digital literacy gaps, economic constraints, and socio-institutional challenges. This study contributes novel insights by contextualizing global AI innovations within Bali’s traditional subak irrigation system, mixed cropping patterns, and tourism-agriculture integration. Recommendations include developing lightweight edge-computing models, participatory technology design with farmer communities, and policy frameworks supporting responsible AI deployment that preserves Bali’s agricultural heritage while enhancing productivity and sustainability
Artificial Intelligence Applications in Agribusiness: Transforming Daily Agricultural Operations for Sustainable Food Systems
The integration of artificial intelligence (AI) in agribusiness has revolutionized daily agricultural operations, offering transformative solutions for sustainable food production. This study examines the practical applications of AI technologies in modern farming, focusing on precision agriculture, crop monitoring, pest detection, and resource management. Through comprehensive analysis of recent implementations, we demonstrate that AI-powered systems achieve 89.5-99.94% accuracy in crop disease detection and agricultural decision support. Computer vision technologies enable real-time identification of plant diseases and pests, while IoT-AI integration reduces water usage by 20-50% and increases crop yields by 15-20%. Machine learning algorithms optimize fertilizer application, reducing costs by 15-30% while maintaining productivity. Despite these advances, implementation challenges persist, including high initial costs, limited technical expertise, and infrastructure constraints in developing regions. This research presents a comprehensive framework for practical AI deployment in agribusiness, emphasizing edge computing solutions, farmer training programs, and collaborative partnerships. The findings demonstrate that strategic AI integration in daily agricultural operations can significantly enhance productivity, sustainability, and resource efficiency while addressing global food security challenges
Transforming Daily Agricultural Food Systems.
Artificial intelligence in Education: Perspective from South African higher education context.
This systematic literature review examines the integration of artificial intelligence (AI) in everyday educational practices within South African contexts, with particular emphasis on teacher and student experiences at institutions like STADIO College of Education and Durban University of Technology, Durban. Through a comprehensive analysis of 30 Scopus-indexed studies published between 2020 and 2026, this research reveals that South African educational institutions employ a diverse array of 57 different technologies, blending mainstream communication platforms (WhatsApp, Zoom, Microsoft Teams) with emergent AI-enabled systems, including automated assessment tools, adaptive learning platforms, and intelligent tutoring systems. The study identifies critical contextual factors unique to South Africa—including infrastructure constraints, the digital divide, socioeconomic disparities, and policy-practice misalignments—that significantly shape AI adoption patterns. While COVID-19 accelerated digital transformation, it simultaneously exposed profound inequities in access and readiness. Teachers demonstrate positive attitudes toward AI integration but face substantial barriers related to skills development, resource limitations, and ethical concerns. This research contributes novel insights by synthesizing South African-specific evidence on everyday AI use, highlighting the tension between technological potential and contextual realities, and proposing equity-centered recommendations for policy and practice
Artificial Intelligence in Daily Banking and Finance: Transforming Customer Experience and Operational Excellence
Artificial intelligence (AI) has fundamentally transformed the financial services landscape, particularly in daily banking operations and customer interactions. This study examines the current state and emerging applications of AI technologies in the banking sector, focusing on practical implementations that directly impact both financial institutions and individual customers. Through a comprehensive literature review of 95 peer-reviewed articles published between 2022 and 2025, this research identifies key AI technologies including natural language processing, deep learning, graph machine learning, and reinforcement learning that are reshaping banking services. The findings reveal that AI-powered applications such as intelligent chatbots, fraud detection systems, automated credit scoring, and personalized financial advisors have significantly enhanced operational efficiency and customer experience. Specifically, advanced fraud detection systems using graph embeddings achieve F1 scores of 67.1%–73.4%, while explainable AI models for ATM fraud detection demonstrate AUC values of 0.963. However, challenges including data privacy, model explainability, regulatory compliance, and algorithmic bias remain significant barriers to adoption. This research contributes to the understanding of AI's practical applications in banking and provides insights for financial professionals at institutions like Akademi Keuangan dan Perbankan Denpasar to prepare for the AI-driven future of financial services
Strategic Management of Artificial Intelligence Integration in Daily Life: A Framework for Personal Productivity Enhancement
The integration of Artificial Intelligence (AI) into daily life has transformed from a futuristic concept into an omnipresent reality, yet the strategic management of these technologies at the individual level remains largely unexplored. This research introduces a novel framework—the Personal AI Management Model (PAMM)—that synthesizes management principles with AI adoption patterns to optimize individual productivity and decision-making in everyday contexts. Through a mixed-methods approach combining surveys of 385 Indonesian respondents and in-depth interviews with 30 active AI users, this study reveals that effective personal AI management requires five critical dimensions: strategic selection, integration planning, performance monitoring, continuous adaptation, and ethical governance. The findings demonstrate that individuals who apply structured management principles to their AI tool adoption achieve 47% higher productivity gains and 63% better satisfaction rates compared to ad-hoc users. This research contributes to management literature by extending organizational AI management frameworks to the personal domain and provides practical insights for individuals, educators, and policymakers in developing countries. The PAMM framework offers a systematic approach for navigating the complex landscape of AI tools in daily life, addressing the critical gap between AI availability and effective utilization.
Artificial Intelligence Integration in Daily Agribusiness Operations: A Paradigm Shift for Tropical Smallholder Farming Systems
The integration of artificial intelligence (AI) in daily agribusiness operations represents a transformative shift in modern agricultural management, particularly for tropical smallholder farming systems. This study examines the novel applications of AI technologies in routine agricultural business activities, focusing on practical implementations that bridge technological innovation with operational feasibility. Through comprehensive analysis of recent developments (2023-2025), we identify four critical domains where AI demonstrates high impact: (1) IoT-enabled precision resource management, (2) autonomous crop monitoring and intervention systems, (3) intelligent farm decision support frameworks, and (4) market-aware supply chain optimization. Field evidence from tropical agriculture settings demonstrates that low-cost AI solutions combining sensor networks, machine learning algorithms, and mobile applications can achieve substantial improvements in resource efficiency (20-30% water savings), productivity (15-20% yield increases), and profitability through optimized crop selection. This research contributes to the growing body of knowledge by synthesizing cutting-edge AI applications specifically contextualized for resource-constrained tropical agribusiness environments, offering actionable insights for smallholder farmers, agricultural extension services, and agribusiness policymakers in developing economies
Democratizing Financial Services: The Role of Artificial Intelligence in Transforming Daily Banking and Personal Finance Management
The integration of artificial intelligence (AI) in banking and finance has fundamentally transformed how individuals interact with financial services in their daily lives. This study examines the democratization of financial services through the application of AI technologies, focusing on machine learning, deep learning, natural language processing, and computer vision. Through systematic analysis of recent literature (2020-2025), this research identifies six core daily-life applications: mobile banking personalization, real-time fraud detection, alternative credit scoring, robo-advisory services, conversational banking interfaces, and intelligent personal finance management. Results indicate that AI enables unprecedented accessibility, personalization, and efficiency in financial services, particularly benefiting underserved populations through the use of alternative data and 24/7 digital access. However, challenges persist regarding data privacy, algorithmic bias, explainability requirements, and regulatory compliance. The study contributes to understanding how AI-driven financial democratization impacts consumer behavior, banking operations, and financial inclusion, with implications for emerging markets seeking to leverage technology for broader economic participation. This research provides practical insights for financial institutions, policymakers, and educators in adapting to the AI-transformed financial landscape.
Implementation of Artificial Intelligence in Intelligent Agricultural Systems for Agrotechnological Transformation for Daily Life
The development of artificial intelligence (AI) technology has brought a significant transformation in the agrotechnology sector, transforming conventional agricultural practices into efficient and sustainable smart farming systems. This research aims to examine the implementation of AI in agrotechnology for farmers' daily life applications. The systematic literature review method was used by analyzing 170 scientific publications indexed by Scopus for the 2022-2025 period. The results of the study show that AI has been implemented in various aspects of agrotechnology including: (1) computer vision-based plant disease detection system with an accuracy of up to 98%, (2) an integrated IoT platform for real-time monitoring of land and plant conditions, (3) a machine learning-based recommendation system for irrigation and fertilization management, (4) UAV technology with deep learning for land mapping and scouting, and (5) digital twin for simulation and optimization of production systems. The implementation of federated learning enables collaboration between farmers in the development of models without compromising data privacy. In conclusion, AI provides practical and affordable solutions to improve productivity, resource efficiency, and sustainability of agriculture in daily life. The implications of this study provide guidance for farmers, practitioners, and academics in adopting AI technology for the transformation of agrotechnology towards smart and sustainable agriculture
Artificial intelligence (AI) has emerged as a transformative technology in modern agrotechnology, addressing critical challenges in food security and sustainable agriculture. This study examines recent innovations in AI applications for daily agricultural practices, focusing on practical implementations that enhance farmer decision-making and operational efficiency. Through a comprehensive analysis of current literature (2023-2025), we identify five key AI application domains: automated irrigation control, crop disease detection, yield prediction, precision farming systems, and explainable AI for crop recommendations. Deep learning techniques, particularly convolutional neural networks (CNNs) and hybrid models, demonstrate superior performance in image-based disease detection (>95% accuracy) and yield forecasting. Edge computing implementations enable real-time decision support even in connectivity-limited environments. The integration of Internet of Things (IoT) sensors with machine learning algorithms facilitates continuous monitoring and automated interventions, reducing labor requirements by 30-40% while improving resource efficiency. Key challenges include data quality, farmer trust, and infrastructure limitations in developing regions. This review synthesizes cutting-edge AI methodologies applicable to Indonesian agricultural contexts, particularly for smallholder farmers, and proposes a framework for sustainable AI adoption in tropical agrotechnology systems. The findings indicate that explainable AI and privacy-preserving federated learning represent critical pathways for widespread adoption, enabling farmers to understand and trust AI-driven recommendations while maintaining data sovereignty
The effectiveness of AI as an adaptive learning tutor to improve student understanding
The development of artificial intelligence (AI) technology presents significant opportunities for adaptive learning innovation, enabling materials to be tailored to individual student needs. However, the effectiveness of AI as an adaptive tutor in increasing student motivation, engagement, and understanding still needs to be analyzed in depth. This research aims to analyze how the use of AI as an adaptive tutor can increase student motivation, engagement, and understanding in the learning process. The research results show that the use of adaptive AI tutoring has a significant positive effect on student motivation and engagement. Motivation acts as a mediator that strengthens the relationship between AI use and student understanding. These findings indicate that AI not only provides appropriate material but also increases students' emotional involvement in learning. This study concludes that AI as an adaptive learning tutor is effective in increasing students' understanding through motivation and engagement. The implications of this research encourage the development and application of AI that is more personal and interactive to support quality and inclusive learning processes.
Model Adaptif Respons Cepat Krisis Deepfake: Kolaborasi Pemerintah–Media Dalam Menghadapi Dampak Perkembangan Kecerdasan Buatan.
Perkembangan teknologi kecerdasan buatan telah memunculkan fenomena deepfake yang mampu memanipulasi informasi secara realistis dan masif, sehingga menimbulkan krisis kepercayaan publik terhadap media dan institusi pemerintah. Kondisi ini menuntut adanya model respons cepat yang adaptif dan kolaboratif agar penyebaran disinformasi dapat diminimalkan secara efektif. Penelitian ini bertujuan untuk merancang dan menganalisis model adaptif respons cepat terhadap krisis deepfake melalui kolaborasi antara pemerintah dan media sebagai strategi mitigasi dampak negatif perkembangan kecerdasan buatan. Penelitian ini menggunakan metode kualitatif dengan desain fenomenologi dan pendekatan aplikatif, yang memungkinkan eksplorasi mendalam terhadap pengalaman dan persepsi aktor kelembagaan dalam menghadapi krisis informasi digital. Populasi penelitian mencakup pejabat pemerintah di bidang komunikasi publik, jurnalis dan redaktur media nasional, serta akademisi yang memahami isu etika kecerdasan buatan. Sebanyak 80 responden dipilih dengan teknik purposive sampling, berdasarkan keterlibatan mereka dalam pengelolaan informasi publik, kebijakan digital, dan produksi konten media. Data dikumpulkan melalui wawancara mendalam, observasi, serta dokumentasi, dan dianalisis menggunakan pendekatan tematik. Hasil penelitian menunjukkan bahwa kolaborasi pemerintah–media masih bersifat parsial, dengan keterlambatan koordinasi dan kurangnya prosedur standar dalam merespons deepfake. Model adaptif yang dihasilkan menekankan tiga elemen utama: kecepatan respons lintas lembaga, transparansi komunikasi publik, dan pembaruan kebijakan berbasis evaluasi berkelanjutan. Kesimpulan penelitian menegaskan bahwa sinergi pemerintah dan media merupakan kunci utama dalam membangun ketahanan informasi publik. Implikasinya, model ini dapat dijadikan kerangka operasional dalam penguatan tata kelola komunikasi krisis digital di era kecerdasan buatan
The Effect of Limited Internet and Electricity Infrastructure on the Utilization of AI in Environmental Data Collection in Remote Areas.
Limited technological infrastructure, especially internet access and electricity supply, is still a serious challenge for remote areas in collecting environmental data effectively. This condition has a direct impact on the region's ability to utilize artificial intelligence (AI) systems that require quality and up-to-date data. This study aims to analyze the influence of limited internet and electricity infrastructure on the effectiveness of the use of AI in the process of collecting environmental data in remote areas using quantitative methods with mediation analysis through the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. Data collection was carried out on community populations and field officers involved in environmental monitoring in remote areas, with a sample of 55 respondents. Respondents were selected using purposive sampling techniques to ensure that all participants had experience or direct involvement in environmental data collection activities. The research instrument is in the form of a questionnaire that includes indicators of infrastructure quality, technology support, and the effectiveness of AI-based data collection. The results show that the limitations of the internet and electricity have a significant negative effect on the effectiveness of data collection required by AI systems. The findings also show that technology support plays a role as a mediating variable that weakens the negative impact of limited infrastructure. In addition, increased technology support has proven to be able to improve the smooth process of data acquisition and delivery, even though the infrastructure is still minimal. In conclusion, limited infrastructure is a major obstacle to maximizing the use of AI in remote areas, but strengthening technology support can reduce this impact. The implications of this study emphasize the need to develop digital infrastructure and increase technological capacity to optimize the use of AI in environmental monitoring.