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All Journal Heca Journal of Applied Sciences Leuser Journal of Environmental Studies Ekonomikalia Journal of Economics Indatu Journal of Management and Accounting PESARE: Science and Engineering Service Journal Grimsa Journal of Business and Economics Studies
Iin Shabrina Hilal
Department Of Civil Engineering, Faculty Of Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Health Professions Medicine & Pharmacology Public Health Social Sciences Other

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Environmental and Economic Clustering of Indonesian Provinces: Insights from K-Means Analysis Noviandy, Teuku Rizky; Hardi, Irsan; Zahriah, Zahriah; Sofyan, Rahmi; Sasmita, Novi Reandy; Hilal, Iin Shabrina; Idroes, Ghalieb Mutig
Leuser Journal of Environmental Studies Vol. 2 No. 1 (2024): April 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v2i1.181

Abstract

Indonesia's archipelago presents a distinctive opportunity for targeted sustainable development due to its complex interplay of economic advancement and environmental challenges. To better understand this dynamic and identify potential areas for focused intervention, this study applied K-means clustering to 2022 data on the Air Quality Index (AQI), electricity consumption, and Gross Regional Domestic Product (GRDP). The analysis aimed to delineate the provinces into three distinct clusters, providing a clearer picture of the varying levels of economic development and environmental impact across the nation's diverse islands. Each cluster reflects specific environmental and economic dynamics, suggesting tailored policy interventions. The results show that for provinces in Cluster 1, which exhibit moderate environmental quality and lower economic activity, the introduction of sustainable agricultural enhancements, eco-tourism, and renewable energy initiatives is recommended. Cluster 2, marked by higher economic outputs and moderate environmental conditions, would benefit from the implementation of smart urban planning, stricter environmental controls, and the adoption of clean technologies. Finally, Cluster 3, which includes highly urbanized areas with robust economic growth, requires expanded green infrastructure, improved sustainable urban practices, and enhanced public transportation systems. These recommendations aim to foster balanced economic growth while preserving environmental integrity across Indonesia’s diverse landscapes.
A Deep Dive into Indonesia's CO2 Emissions: The Role of Energy Consumption, Economic Growth and Natural Disasters Idroes, Ghalieb Mutig; Hardi, Irsan; Noviandy, Teuku Rizky; Sasmita, Novi Reandy; Hilal, Iin Shabrina; Kusumo, Fitranto; Idroes, Rinaldi
Ekonomikalia Journal of Economics Vol. 1 No. 2 (2023): November 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/eje.v1i2.115

Abstract

This study examines the influence of non-renewable energy consumption, renewable energy consumption, economic growth, and natural disasters on Indonesia's carbon dioxide (CO2) emissions spanning from 1980 to 2021. The Autoregressive Distributed Lag (ARDL) model is employed, with supplementary robustness checks utilizing Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR). The findings reveal that economic growth, along with non-renewable and renewable energy consumption, significantly affects CO2 emissions in both the short and long term. Robustness checks confirm the positive impact of non-renewable energy consumption and economic growth, while renewable energy consumption has a negative effect on CO2 emissions. Moreover, natural disasters exhibit a positive short-term impact on CO2 emissions. Pairwise Granger causality results further underscore the intricate relationships between the variables. To mitigate climate change and curb CO2 emissions in Indonesia, the study recommends implementing policies that foster sustainable economic development, encourage the adoption of renewable energy, and enhance disaster resilience.
Do Natural Disasters, Fossil Fuels, and Renewable Energy Affect CO2 Emissions and the Ecological Footprint? Idroes, Ghalieb Mutig; Hilal, Iin Shabrina; Hafizah, Iffah; Hamaguchi, Yoshihiro; Bruyn, Chané de; Agustina, Maulidar; Pernici, Andreea; Stancu, Stelian
Ekonomikalia Journal of Economics Vol. 3 No. 1 (2025): April 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/eje.v3i1.285

Abstract

Climate change is a global concern driven by increasing pollution through rising CO2 emissions and growing ecological footprint from human activities. This research investigates how environmental quality (proxied by CO2 emissions and ecological footprint) in Indonesia is affected by multiple factors, including natural disasters, fossil fuels, renewable energy consumption, economic growth, and capital formation from 1965 to 2022. The analysis employs the Autoregressive Distributed Lag (ARDL) model, with robustness ensured using Dynamic Ordinary Least Squares (DOLS), followed by Granger causality tests to examine dynamic relationships between variables. The findings show that natural disasters, fossil fuel consumption, and economic growth contribute to increasing CO2 emissions in the long run, while renewable energy consumption helps reduce them. Natural disasters exhibit a negative but insignificant impact on the ecological footprint. Economic growth increases the ecological footprint, whereas capital formation helps reduce it in the long run. In the short run, fossil fuels are found to increase CO2 emissions, while renewable energy reduces them. Natural disasters are found to increase the ecological footprint. Additionally, the Granger causality test confirms a unidirectional relationship from both natural disasters and economic growth to environmental quality. This study recommends that Indonesia implement integrated strategies focused on accelerating green energy adoption and enhancing disaster resilience to achieve environmental quality.
Kajian Risiko IBPRP dalam Perencanaan Pekerjaan Pengerukan Pemeliharaan Kolam Pelabuhan Ulee Lheue Ibdayanti, Dinda Rizka; Mubarak, Mubarak; Fatimah, Eldina; Sari Mastura, Cut Annisa Widya; Aulia Kesuma, Putra; Humayra, Siti; Shabrina Hilal, Iin
PESARE: Jurnal Pengabdian Sains dan Rekayasa Vol 3, No 2 (2025): Juni 2025
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/pesare.v3i2.45377

Abstract

The maintenance dredging work at Ulee Lheue Port aims to maintain optimal water depth for navigation activities. However, this activity involves various risks that must be systematically identified and managed. This study employs the IBPRP (Hazard Identification, Risk Assessment, and Opportunities) method to analyze potential risks in the dredging process.The analysis results indicate four major risks, consisting of two medium-level risks and two high-level risks, with no low-level risks identified. The high-level risks have the potential to significantly impact the stability of the port basin and worker safety. To mitigate these risks, strategies adhering to occupational safety standards and environmental protection measures are implemented, such as the adoption of safer dredging technologies, strict operational supervision, and workforce training.By implementing appropriate risk identification and mitigation measures, the dredging process can be carried out more safely, efficiently, and sustainably. This study is expected to serve as a reference for port management in designing more optimal and risk-based dredging strategies
Agrochemicals, GHG Emissions, and GDP in Southeast Asia: A Machine Learning Approach with Hierarchical Clustering Fazli, Qalbin Salim; Idroes, Ghalieb Mutig; Hilal, Iin Shabrina; Hafizah, Iffah; Hardi, Irsan; Noviandy, Teuku Rizky
Grimsa Journal of Business and Economics Studies Vol. 2 No. 2 (2025): July 2025
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjbes.v2i2.93

Abstract

Agrochemical use, GHG emissions, and gross domestic product (GDP) vary widely across Southeast Asia, making the region suitable for cluster-based sustainability analysis. This study applies hierarchical clustering analysis (HCA) to classify nine Southeast Asian countries using four standardized indicators: pesticide use, nitrogen fertilizer use, GHG emissions, and GDP. Exploratory data analysis reveals significant disparities, with Brunei and Indonesia emerging as outliers due to exceptionally high input intensity and emissions, respectively. HCA identifies four distinct clusters: (1) low-input, low-emission economies (Cambodia, Laos, Myanmar); (2) moderately intensive systems (Malaysia, Thailand, the Philippines, Vietnam); (3) a high-pesticide profile (Brunei); and (4) a high-emission, high-output outlier (Indonesia). Principal Component Analysis confirms the cluster structure and highlights variation in emission efficiency. The findings show that similar agroecological contexts can yield divergent environmental outcomes, emphasizing the role of policy and technology. This study provides the first region-wide, data-driven typology of agricultural sustainability in Southeast Asia using HCA.
Top Global Concrete-Producing Countries: A Hierarchical Cluster Analysis of Concrete Production, CO2 Emissions, and Economic Growth Hilal, Iin Shabrina; Idroes, Ghalieb Mutig
Heca Journal of Applied Sciences Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v3i2.314

Abstract

Concrete production plays a vital role in infrastructure and economic development, yet it remains one of the most significant sources of global CO2 emissions. This study focuses on the top 10 concrete-producing countries, using variables such as concrete production (CP), carbon dioxide (CO2) emissions, and gross domestic product (GDP) as a proxy for economic growth. Using hierarchical cluster analysis, we categorize the countries into three distinct groups based on the combined metrics. Cluster 1 includes developing and transitional economies such as India, Indonesia, Brazil, Egypt, Russia, Turkey, and Vietnam, which exhibit moderate levels of CP and GDP alongside relatively low CO2 per capita. Cluster 2, represented by China and Saudi Arabia, demonstrates high levels of CP and CO2, coupled with moderate to high GDP, reflecting intensive industrial activity and rapid development. Cluster 3, which includes only the United States, is characterized by high GDP, moderate CP, and persistently high CO2, indicating a stable developed economy that maintains its prosperity through infrastructure upkeep rather than rapid growth. The findings reveal how these three indicators interact across different stages of development and emphasize the importance of tailored sustainability strategies.
How Is Research Connecting Artificial Intelligence, Sustainability Governance, and Agri-Food Supply Chains Evolving? A Bibliometric Analysis Salim Fazli, Qalbin; Isaack Delya, Mussa; Hironimus Kihwili, Erick; Qashmal, Muhammad; Shabrina Hilal, Iin; Idroes, Ghalieb Mutig
Indatu Journal of Management and Accounting Vol. 3 No. 2 (2025): December 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v3i2.368

Abstract

This study examines the development of research situated at the intersection of artificial intelligence, sustainability governance, and agri-food supply chains through a comprehensive bibliometric analysis of 988 Scopus-indexed articles published between 2017 and 2025. This time range was selected because scholarly attention to artificial intelligence in sustainability and agri-food systems began to intensify after 2017, alongside the emergence of Industry 4.0, data-driven governance frameworks, and circular economy agendas, allowing the analysis to capture both the formative and consolidation phases of this research domain. A structured search, screening, and eligibility process was applied to ensure thematic relevance and methodological rigor, followed by performance analysis and science-mapping techniques using VOSviewer, CiteSpace, and complementary normalization procedures. The findings reveal accelerating publication growth, concentrated collaboration networks, and thematic convergence around digital sustainability, circularity, and data-driven supply-chain optimization. Keyword and citation structures indicate that the field increasingly integrates technological and environmental perspectives, although research contributions remain unevenly distributed across authors, institutions, and countries. The study highlights the emergence of a more coherent knowledge base while underscoring the need for broader participation and deeper conceptual synthesis. These insights provide a consolidated foundation for guiding future work toward stronger theoretical development and more impactful applications in sustainable agri-food systems.
Co-Authors Agustina, Maulidar Aulia Kesuma, Putra Bruyn, Chané de Eldina Fatimah Fazli, Qalbin Salim Hafizah, Iffah Hamaguchi, Yoshihiro Hironimus Kihwili, Erick Humayra, Siti Ibdayanti, Dinda Rizka Idroes, Ghalieb Mutig Irsan Hardi Isaack Delya, Mussa Kusumo, Fitranto Mubarak Mubarak Pernici, Andreea Qashmal, Muhammad Rinaldi Idroes Salim Fazli, Qalbin Sari Mastura, Cut Annisa Widya Sasmita, Novi Reandy Sofyan, Rahmi Stancu, Stelian Sugeng Santoso Teuku Rizky Noviandy Zahriah, Zahriah