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  • The Role of Environmental Policy in Promoting Green Transportation Technologies

    The Role of Environmental Policy in Promoting Green Transportation Technologies

    Authors: Suthakavatin, Siphimvadee ; Shatila, Khodor ; Aydinyan, Karine ; Santy, Raeni Dwi

    DOI: 10.1051/bioconf/202414506013

    Abstract:

    This study explores the role of environmental policy in promoting the adoption of green transportation technologies, focusing on the effects of financial incentives, regulatory frameworks, and public investment in infrastructure across key Asian urban centres. The research highlights how technological innovation acts as a crucial mediator between policy measures and the adoption of sustainable transportation options such as electric vehicles (EVs) and hydrogen-powered vehicles. Using Structural Equation Modelling (SEM), the study examines the relationships between these factors, demonstrating that higher levels of financial incentives, supportive regulations, and strategic public investment lead to significant advancements in technological innovation, which in turn drives the adoption of green transportation technologies. The findings contribute to the broader understanding of sustainable urban mobility solutions and offer important insights for policymakers and industry stakeholders in regions experiencing rapid urbanization. The study also discusses the dual role of these policy drivers, both in directly influencing adoption and in fostering technological advancement. © The Authors, published by EDP Sciences.

  • Geospatial Intelligence Framework for BTS Infrastructure Planning Toward Universal Internet Access Target in Indonesia

    Geospatial Intelligence Framework for BTS Infrastructure Planning Toward Universal Internet Access Target in Indonesia

    Authors: Sakti, Anjar Dimara ; Ayu Andani, I Gusti ; Putri, Anissa Dicky ; Zakiar, Muhammad Rizky ; Faruqi, Ismail Al; Santoso, Cokro ; Caraka, Rezzy Eko ; Rohayani, Pitri ; Pramudya, Fabian Surya ; Wijayanto, Arie Wahyu ; Setiyadi, Angga ; Shalannanda, Wervyan

    DOI: 10.1016/j.jag.2024.104274

    Abstract:

    Equitable internet coverage has emerged as a key global priority, which is essential for promoting inclusive and sustainable development. The Indonesian government aims to provide universal internet access by 2024, particularly in remote regions. This study introduces a novel machine-learning-based approach to identify the priority areas for deploying Base Transceiver Station (BTS) towers, which are crucial for achieving the internet access targets of the government. A BTS Network Priority Index was developed by integrating the internet demand estimates with a BTS suitability index derived from key predictors: proximity to fiber optic stations, physical–environmental suitability, and infrastructure–economic readiness. The model identified areas with high internet demand and high BTS suitability as the most critical for immediate development, covering 20 km2. Additionally, future BTS development should target areas with high demand but medium suitability (900 km2) and medium demand but high suitability (280 km2). To validate the methodology, the Random Forest model was employed, which achieved an area under the curve value of 0.7315, indicating strong predictive performance. For the BTS Deployment Suitability parameter, the median was 0.65, with the lower and upper quartiles at 0.44 and 0.85, respectively, confirming that most proposed locations are highly suitable for development. This systematic approach provides data-driven insights for the equitable distribution of BTS towers to ensure efficient internet infrastructure expansion across Indonesia. Furthermore, the study offers a framework that can be adapted by other countries aiming to improve their digital infrastructure and achieve comprehensive, equitable internet access. © 2024 The Author(s)

    Author Keywords:

    Internet accessibility; Machine learning; Remote sensing; Spatial assessment

    Indexed Keywords:

    Regional Index

    Indonesia

    GEOBASE Subject Index

    infrastructure planning; Internet; machine learning; remote sensing; sustainable development

  • Advancing Language Education in Indonesia:

    Integrating Technology and Innovations

    Authors: Luckyardi, Senny ; Munawaroh, Silvi ; Abduh, Amirullah; Rosmaladewi R. ; Hufad, Achmad ; Haristian, Nuria

    DOI: 10.17509/ajse.v4i3.79471

    Abstract:

    Language learning in Indonesia’s educational environment is accelerating change due to the introduction of novel technologies and teaching methods. This paper analyzed the essential functions of digital tools, the internet, and contemporary educational approaches to enhancing Indonesian language learning results. When considering the challenges of low penetration in remote areas and fluctuating technological maturity, opportunities exist to explore the potential of technology to bridge the language acquisition gap. Drawing on a review of several projects (i.e., mobile applications, e-learning platforms, and artificial intelligence (AI)-driven language support), the current study outlines their success in fostering multilingualism, enhancing engagement rates, and developing mother tongue and second language skills. The outcome suggests that education through language for Indonesian learners will be successful if there is a balance between traditional teaching advantages, such as face-to-face teaching, and modern technology’s power and freedom. Policies, pedagogical, and institutional ideas are proposed to build a sustainable, inclusive, and dynamic model for a language education framework based on the sake of its citizenry. © 2024 Universitas Pendidikan Indonesia.

    Author Keywords:

    Education; Indonesia; Language; Technology

  • A Knowledge Capabilities Financial Model Based on the Performance

    of Fashion Enterprises: Micro, Small, and Medium

    Authors: Novianti, Windi ; Narimawati, Umi ; Ahiase, Godwin ; Pramuditha, Panji

    DOI: 10.14453/AABFJ.V19I2.05

    Abstract:

    This study investigates the relationship between financial knowledge capability and MSME performance in West Java, Indonesia, and explores the mediating role of digital marketing and intelligent financial technology. Structural equation modeling was utilized to analyze 375 MSMEs, revealing a significant impact of Financial Knowledge Capability on MSME’s performance. Moreover, the study finds that digital marketing and intelligent financial technology mediate this relationship positively, with digital marketing awareness of utilizing intelligent financial technology identified as a key determinant of MSME performance. This research shows that with efforts to improve the role of digital marketing effectively, MSMEs can increase their competitiveness in the market and grow their business significantly. Intelligent Financial Technology allows MSMEs to access financial services such as loans, payments, and investments more easily and quickly. It concludes that specific strategies can be implemented to maximize these contributions. © 2025, University of Wollongong. All rights reserved.

    Author Keywords:

    Digital Marketing; Intelligent Financial Technology; Knowledge Capabilities Financial; MSMEs Performance

  • Governing AI-Driven Agriculture: Policy, Ethics, and

    the Role of Language in Knowledge Transfer

    Authors: Zangana, Hewa Majeed ; Amelia, Pratiwi ; Luckyardi, Senny ; Mustafa, Firas Mahmood ; Li, Shuai 

    DOI: 10.4018/979-8-3373-4862-9.ch011

    Abstract:

    Artificial intelligence (AI) is transforming agriculture by enabling precision farming, predictive analytics, and automated decision-making, thereby enhancing productivity and sustainability. However, this rapid technological advancement raises complex policy and ethical challenges, particularly regarding data governance, equitable access, environmental impact, and transparency. This chapter explores the regulatory frameworks shaping AI-driven agricultural practices and emphasizes the critical role of language in facilitating effective knowledge transfer among diverse stakeholders, including farmers, policymakers, and researchers. By analyzing interdisciplinary approaches, the chapter highlights how linguistic clarity and ethical considerations underpin responsible AI governance in agriculture, ensuring innovations serve public interest while mitigating risks. Ultimately, it advocates for comprehensive policies that balance innovation with accountability and inclusivity in the evolving landscape of agri-tech. © 2025, IGI Global Scientific Publishing.

    Indexed Keywords:

    Engineering controlled terms

    Agribusiness; Agriculture; Artificial intelligence; Decision making; Environmental impact; Ethical technology; Knowledge management; Knowledge transfer; Smart agriculture; Sustainable agriculture; Sustainable development

    Engineering uncontrolled terms

    Agricultural practices; Automated decision making; Data governances; Environmental transparency; Equitable access; Knowledge transfer; Policy makers; Precision-farming; Regulatory frameworks; Technological advancement

    Engineering main heading

  • Contributing Factors to Greenhouse Gas Emissions in Agriculture for Supporting Sustainable Development Goals (SDGs): Insights from a Systematic Literature Review Completed by Computational Bibliometric Analysis

    Contributing Factors to Greenhouse Gas Emissions in Agriculture for Supporting Sustainable Development Goals (SDGs): Insights from a Systematic Literature Review Completed by Computational Bibliometric Analysis

    Authors: Soegoto, Herman S. ; Pohan, Muhammad Aria Rajasa ; Luckyardi, Senny ; Supatmi, Sri ; Amasawa, Eri ; Phithakkitnukoon, Santi ; Hasibuan, Zainal Arifina

    DOI: 10.17509/ajse.v5i2.83667

    Abstract:

    Agricultural production contributes significantly to greenhouse gas (GHG) emissions and global climate change. This study conducts a systematic literature review to examine the evolution and drivers of agricultural GHG emissions. We analyzed Web of Science, Scopus, and Google Scholar data using bibliometric and thematic methods. Our analysis identified emission sources such as energy use, soil management, fertilizer application, and livestock management. It also discussed mitigation measures such as sustainable practices, precision agriculture, and renewable energy. The findings showed that crop cultivation, livestock activities, and land-use change remained key sources of emissions. Technological innovations and policy-driven strategies are reshaping the research landscape. This study provides a framework for understanding agricultural GHG emissions and supporting interventions to reduce the sector’s carbon footprint as well as Sustainable Development Goals (SDGs). © 2025 Kantor Jurnal dan Publikasi UPI.

    Author Keywords:

    Agricultural production; Emission sources; Greenhouse gas emissions; Mitigation strategies; Sustainable development goals (SDGs); Sustainable practices; Systematic literature review

  • Marketing Strategy of Ecotourism in Uzbekistan and Indonesia

    Marketing Strategy of Ecotourism in Uzbekistan and Indonesia

    Authors: Novia Yuliarni, Ratih Hurriyati, Disman, Heny Hendrayati, Lia Warlina

    DOI: 10.15549/jeecar.v10i4.1359

    Abstract

    This study aims to compare a marketing strategy for ecotourism in Uzbekistan and Indonesia. A marketing strategy study for ecotourism in Uzbekistan used a literature review. However, ecotourism in Indonesia used a model to examine how the ecotourism experience influences tourist satisfaction and loyalty. The authors used structural equation modeling with 400 tourists who have visited the Kawah Putih Ecotourism in West Java, Indonesia. According to study findings, Uzbekistan’s ecotourism industry has a more significant positive impact on the nation’s economy and society. The results show that a positive ecotourism experience in Indonesia increases tourist satisfaction and loyalty, which is essential in marketing strategy. The impact of this research is that all stakeholders in the ecotourism sector should improve marketing strategies that can increase tourist satisfaction. As a result, the tourists will repeat visits to other ecotourism destinations. © 2023, Institute of Eastern Europe and Central Asia. All rights reserved.

    Keywords: destination loyalty; ecotourism; marketing; satisfaction; tourism experience

    This article can be accessed at https://www.scopus.com/pages/publications/85164109617

  • Investment Promotion Strategy of Tourism and Agriculture Sector to Promote Regional Competitiveness

    Investment Promotion Strategy of Tourism and Agriculture Sector to Promote Regional Competitiveness

    Authors: Lia Warlina, Kankan Kasmana, Selfa Septiani Aulia, Muhammad Iffan, Winy Noer Widiashanty

    DOI: 10.15549/jeecar.v10i6.1498

    Abstract

    This study aims to identify an investment promotion strategy for the agriculture and tourism sector with the case study of Sumedang Regency in West Java Province, Indonesia. A literature review and a focus group discussion with the stakeholders were used to identify the promotion had been conducted and to formulate investment promotion strategies. The result from Vosviewer shows that studies in investment promotion strategy in agriculture and tourism were relatively low. Promotion in the agricultural sector is less than in the tourism sector, and the current promotion in agriculture is tied to tourism, such as agrotourism. The formulated investment promotion strategy for agriculture and tourism was brand activation, consisting of experiential and digital marketing and personal selling. Success in executing this investment promotion plan must consider a favorable investment environment, such as the facilities and incentives, to encourage regional competitive advantage. © 2023, Institute of Eastern Europe and Central Asia. All rights reserved.

    Keywords: agriculture; investment; promotion strategy; tourism

    This article can be accessed at https://www.scopus.com/pages/publications/85178278292

  • Evaluation of Cimahi City as a Sustainable City Using GIS (Case Study: Cipageran and Citeureup Planning Area)

    Evaluation of Cimahi City as a Sustainable City Using GIS (Case Study: Cipageran and Citeureup Planning Area)

    Authors: Selfa Septiani Aulia, Amilia Widya, Rifiati Safariah, Nadya Nanda Prawila

    DOI: 10.1109/INCITEST64888.2024.11121465

    Abstract

    Cimahi City is one of the cities in West Java Province that has problems with flooding, slum areas, clean water crises, traffic jams, and land conversions. Currently, every city is required to be able to increase development sustainably. The purpose of this study is evaluation of the sustainable development of Cimahi City based on infrastructure, settlements, and transportation in Cimahi City. The Geographic Information System Method was used to identified the patterns of existing infrastructure, settlements, and transportation in Cimahi. Importance Performance Analysis was used to evaluation the sustainable development in Cimahi. The results are infrastructures from waste management has been done by the community but still needs improvements. The sustainable transportations management and the settlements must improve its services. © 2024 IEEE.

    Keywords: GIS method; IPA method; sustainable city; urban planning

    This article can be accessed at https://www.scopus.com/pages/publications/105015877951

  • Comparative Study of K-Means and Mean Shift Clustering Algorithms for Waste Data in West Java Province

    Authors: Rony Setyawan, Geraldi Catur Pamuji

    Abstract

    This study presents a comprehensive comparative analysis of the k-Means and Mean Shift clustering algorithms, utilizing waste data collected from West Java Province’s final disposal site spanning 2016 to 2021, with the primary objective of evaluating their performance and applicability for waste management practices; the analysis encompasses several critical parameters, including the number of clusters generated, variable uniformity, evaluation metrics employed, divergence measures, and processing time efficiency, revealing that k-Means, which formed three clusters, excels in rapid processing and provides finer cluster division, while Mean Shift, yielding two clusters, offers nuanced insights into data patterns, leading to the recommendation that the choice between the two algorithms should be driven by specific project requirements and considerations such as urgency of waste management needs and the depth of understanding desired for effective decision-making, thereby offering a tailored approach to waste data organization that optimizes categorization and contributes to more efficient and sustainable waste disposal practices in the future. © School of Engineering, Taylor’s University.

    Keywords: k-means clustering; Mean shift clustering; Waste data

    This article can be accessed at https://www.scopus.com/pages/publications/85197577372