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All Journal PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS (COMORBID) TRANSPUBLIKA INTERNATIONAL RESEARCH IN EXACT SCIENCES (TIRES) Jurnal Pengabdian Masyarakat Bangsa Heca Journal of Applied Sciences Malacca Pharmaceutics Leuser Journal of Environmental Studies Ekonomikalia Journal of Economics Journal of Educational Management and Learning Infolitika Journal of Data Science Grimsa Journal of Science Engineering and Technology Grimsa Journal of Business and Economics Studies
Ghazi Mauer Idroes
Department Of Occupational Health And Safety, Faculty Of Health Sciences, Universitas Abulyatama, Aceh Besar 23372, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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Journal : Leuser Journal of Environmental Studies

 1 
Utilization of Drone with Thermal Camera in Mapping Digital Elevation Model for Ie Seu'um Geothermal Manifestation Exploration Security Bahri, Ridzky Aulia; Noviandy, Teuku Rizky; Suhendra, Rivansyah; Idroes, Ghazi Mauer; Yanis, Muhammad; Yandri, Erkata; Nizamuddin, Nizamuddin; Irvanizam, Irvanizam
Leuser Journal of Environmental Studies Vol. 1 No. 1 (2023): July 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i1.40

Abstract

Geothermal energy is a viable alternative energy source, particularly in Indonesia. This study was conducted at Ie Seu’um, Mount Seulawah Agam, which is a potential site for a geothermal power plant with an estimated electrical output of 150 megawatts. The objective of this study was to analyze and construct a digital elevation model (DEM) map of the geothermal manifestations. We analyzed water temperature, FLIR (Forward Looking Infrared) temperature, and temperature data from Landsat 8 satellite imagery. To map the heat signature of geothermal features, we utilized the DJI Phantom 4 Standard equipped with the FLIR One Gen 2 sensor. Additionally, we used the Milwaukee Mi306 to calculate the water temperature. Each test was conducted three times to obtain an optimal average level of accuracy. The DEM map was created to assess the level of safety in geothermal manifestation exploration. Elevation and slope values were analyzed to generate a 3D map display, providing a clearer image of the research site. In conclusion, drones prove to be an excellent method for ensuring the safety of exploration in geothermal manifestation areas.
TeutongNet: A Fine-Tuned Deep Learning Model for Improved Forest Fire Detection Idroes, Ghazi Mauer; Maulana, Aga; Suhendra , Rivansyah; Lala, Andi; Karma, Taufiq; Kusumo, Fitranto; Hewindati, Yuni Tri; Noviandy, Teuku Rizky
Leuser Journal of Environmental Studies Vol. 1 No. 1 (2023): July 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i1.42

Abstract

Forest fires have emerged as a significant threat to the environment, wildlife, and human lives, necessitating the development of effective early detection systems for firefighting and mitigation efforts. In this study, we introduce TeutongNet, a modified ResNet50V2 model designed to detect forest fires accurately. The model is trained on a curated dataset and evaluated using various metrics. Results show that TeutongNet achieves high accuracy (98.68%) with low false positive and false negative rates. The model's performance is further supported by the ROC curve analysis, which indicates a high degree of accuracy in classifying fire and non-fire images. TeutongNet demonstrates its effectiveness in reliable forest fire detection, providing valuable insights for improved fire management strategies.
Exploring Geothermal Manifestations in Ie Jue, Indonesia: Enhancing Safety with Unmanned Aerial Vehicle Aprianto, Aprianto; Maulana, Aga; Noviandy, Teuku Rizky; Lala, Andi; Yusuf, Muhammad; Marwan, Marwan; Afidh, Razief Perucha Fauzie; Irvanizam, Irvanizam; Nizamuddin, Nizamuddin; Idroes, Ghazi Mauer
Leuser Journal of Environmental Studies Vol. 1 No. 2 (2023): November 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i2.75

Abstract

Geothermal energy is a renewable resource derived from the Earth's interior that provides an environmentally friendly alternative. Indonesia is at the forefront of geothermal potential, possessing ample resources primarily concentrated in places like Sumatra. However, there is a requirement for greater exploitation of this potential. This research utilizes unmanned aerial vehicles (UAVs) and thermal imaging to detect geothermal indications in the Ie Jue region of Sumatra within the province of Aceh, Indonesia. The analysis focuses on three main manifestation locations using FLIR One thermal camera and water temperature gauges. The study leverages satellite imagery for comparative purposes. Temperature data highlights variations among distinct manifestations, underscoring the necessity for thorough exploration. Moreover, the study devises a secure pathway for researchers to access the site. This investigation contributes to comprehending geothermal activity and its possible role in sustainable energy and other domains.
Urban Air Quality Classification Using Machine Learning Approach to Enhance Environmental Monitoring Idroes, Ghazi Mauer; Noviandy, Teuku Rizky; Maulana, Aga; Zahriah, Zahriah; Suhendrayatna, Suhendrayatna; Suhartono, Eko; Khairan, Khairan; Kusumo, Fitranto; Helwani, Zuchra; Abd Rahman, Sunarti
Leuser Journal of Environmental Studies Vol. 1 No. 2 (2023): November 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v1i2.99

Abstract

Urban areas worldwide grapple with environmental challenges, notably air pollution. DKI Jakarta, Indonesia's capital city, is emblematic of this struggle, where rapid urbanization contributes to increased pollutants. This study employed the CatBoost machine learning algorithm, known for its resistance to overfitting and capability to handle missing data, to predict urban air quality based on pollutant levels from 2010 to 2021. The dataset, sourced from Jakarta's air quality monitoring stations, includes pollutants such as PM10, SO2, CO, O3, and NO2. After preprocessing, we used 80% of the data for training and 20% for testing. The model displayed high accuracy (0.9781), precision (0.9722), and recall (0.9728). The feature importance chart revealed O3 (Ozone) as the top influencer of air quality predictions, followed by PM10. Our findings highlight the dominant pollutants affecting urban air quality in Jakarta, Indonesia and emphasizing the need for targeted strategies to reduce their concentrations and ensure a cleaner and healthier urban environment.
Ensuring Accuracy: Critical Validation Techniques in Geochemical Analysis for Sustainable Geothermal Energy Development Idroes, Ghazi Mauer; Suhendrayatna, Suhendrayatna; Khairan, Khairan; Suhartono, Eko; Prasetio, Rasi; Riza, Medyan
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.v2i1.176

Abstract

Geochemical analysis is a critical tool in geothermal exploration, providing valuable insights into reservoir characteristics. However, obtaining accurate and reliable geochemical data requires rigorous validation techniques. This review examines key factors affecting the accuracy of geochemical data and discusses best practices for ensuring quality. Proper sampling methods, including selection of representative locations, use of appropriate equipment, and adherence to robust protocols for sample collection, filtration, preservation, and storage, are essential for maintaining integrity. Analytical techniques must be carefully selected, with regular calibration and standardization of instruments using certified reference materials. Implementing comprehensive quality assurance and quality control procedures, such as analyzing blanks, duplicates, and spike samples, helps monitor precision and accuracy. Data interpretation should consider the complexities of the geological and hydrological settings, integrating multiple lines of evidence. By following established guidelines and continuously updating methods based on emerging technologies and inter-laboratory comparisons, geothermal teams can optimize the reliability of their geochemical data. Accurate and precise geochemical information, when combined with geological, geophysical, and hydrological data, enables informed decision-making and enhances the success of geothermal projects. As geothermal energy gains importance in the transition to sustainable resources, ensuring the accuracy of geochemical analysis will be crucial for effective exploration and development.
Influence of Elevational and Environmental Factors on Parasitic Nematode Distribution in Arabica Coffee in the Gayo Highlands, Indonesia Surna, Muhammad Ipan; Fazli, Qalbin Salim; Chamzurni, Tjut; Susanna, Susanna; Idroes, Ghazi Mauer
Leuser Journal of Environmental Studies Vol. 3 No. 2 (2025): October 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v3i2.293

Abstract

Highland agricultural landscapes are sensitive to environmental variation, particularly in regions like the Gayo Highlands of Aceh, Indonesia, where Arabica coffee (Coffea arabica L.) is a major crop. While parasitic nematodes are known to affect crop health and soil ecosystems, little is known about how their abundance and distribution vary with elevation in tropical coffee systems. The Gayo Highlands, despite their significant contribution to national coffee production, have been understudied in terms of soil biodiversity and nematode-related threats. To address this knowledge gap, we assessed the composition and abundance of parasitic nematodes in coffee plantations across three elevation zones: 800–1000 m, 1001–1200 m, and 1201–1400 m above sea level. We collected soil and root samples from symptomatic coffee plants, extracted nematodes using the Baermann funnel method, and identified them to the genus level. The study found three genera: Pratylenchus, Meloidogyne, and Rotylenchus. Pratylenchus was the most abundant, particularly at 800–1,000 m (34 individuals/10 ml), while the highest total nematode abundance occurred at 1,001–1,200 m (7.2 ± 1.44 individuals/10 ml). Statistical analysis showed significant differences in nematode abundance between elevation zones. These results indicate that elevation influences nematode populations, likely through environmental factors such as temperature, soil moisture, and pH. Understanding these patterns is important for developing site-specific strategies for pest management and maintaining soil health in highland coffee systems.
Resilience and Adaptation: Plant Ecology in Indonesia’s Geothermal Environments Idroes, Ghazi Mauer; Khairan, Khairan; Suhartono, Eko; Prasetio, Rasi; Idroes, Ghalieb Mutig; Suhendrayatna, Suhendrayatna
Leuser Journal of Environmental Studies Vol. 3 No. 1 (2025): April 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v3i1.294

Abstract

Geothermal ecosystems are defined by extreme environmental conditions, such as elevated temperatures, high concentrations of toxic chemicals, and fluctuations in abiotic stressors, which shape plant survival and adaptation. These unique ecosystems, found across various geothermal regions globally, support specialized plant communities that have developed distinctive morphological, physiological, and ecological adaptations. Indonesia, located on the Pacific Ring of Fire, is one of the world’s richest geothermal nations, offering an important yet underexplored context for studying vegetation in geothermal zones. This review examines the environmental conditions of geothermal ecosystems, the adaptive strategies of vegetation, and patterns of plant diversity within Indonesian geothermal fields. It also explores ecological succession, community dynamics, and the potential use of geothermal vegetation as environmental indicators for biomonitoring. Despite growing interest, significant research gaps remain, particularly in long-term monitoring and the integration of molecular-level studies. Addressing these gaps is essential for enhancing scientific understanding and informing conservation and sustainable geothermal energy development in tropical regions. This review highlights the ecological significance of geothermal vegetation and underscores the need for interdisciplinary research to support both biodiversity preservation and responsible energy exploitation.
Environmental Influence of Altitude on Coffee Leaf Rust Severity in Arabica Coffee of Aceh Tengah, Indonesia Arkadinata, Teguh; Fazli, Qalbin Salim; Alfizar, Alfizar; Hakim, Lukman; Idroes, Ghazi Mauer
Leuser Journal of Environmental Studies Vol. 3 No. 2 (2025): October 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v3i2.344

Abstract

Coffee leaf rust (CLR), caused by Hemileia vastatrix, remains one of the most damaging diseases affecting Arabica coffee worldwide. Understanding how environmental gradients influence CLR development is critical for sustainable management in tropical highland systems. This study examined the influence of altitude on CLR incidence and severity across five elevation ranges (800–1800 masl) in Arabica coffee plantations of Aceh Tengah, Indonesia. Field assessments were conducted on 25 farms using a standardized sampling layout and severity scoring scale. Analysis of variance (ANOVA) revealed that altitude had no significant effect on disease incidence (F = 0.14 < F0.05 = 3.01), which remained uniformly high across all sites (>75%), but significantly affected disease severity (F = 3.34 > F0.05 = 3.01). The highest mean severity (51.88%) occurred at 1600–1800 masl, differing significantly from lower elevations. These findings suggest that while CLR infection frequency is widespread, environmental conditions at higher altitudes favor greater lesion expansion and disease development. The results highlight the importance of considering local microclimatic variability in disease risk assessment and adaptive management. Further studies integrating microclimatic and agronomic measurements are needed to strengthen causal understanding and support environmentally based strategies for sustainable Arabica coffee production.
Co-Authors Abas, Abdul Hawil Abd Rahman, Sunarti Ahmad, Noor Atinah Akmal Muhni Alfizar Alfizar Ali Bakri Anggi, Tiara Aprianto . Arkadinata, Teguh Asep Rusyana Azhar, Fauzul Bachtiar, Boy Muhclis Bahri, Ridzky Aulia Bako, Winanda Celik, Ismail Delya, Mussa Issack Diah, Muhammad Diana Setya Ningsih, Diana Diana Setya Ningsih, Diana Setya Diki, Diki Eko Suhartono El-Shazly, Mohamed Emran, Talha Bin Erkata Yandri Faisal, Farassa Rani Fajar Fakri Fauziah, Niken Fazli, Qalbin Salim Hafni Zahara Harahap, Saima Putri Harera, Cheariva Firsa Hewindati, Yuni Tri Hizir Sofyan Idroes, Ghalieb Mutig Ifandi, Ilham Imelda, Eva Irvanizam, Irvanizam Irwana, Salman Jainury, Aldi Jauna, Jauna Kemala, Pati Khairan Khairan Khalijah Awang Kihwili, Erick Hironimus Kurniadinur, Kurniadinur Kusumo, Fitranto Lala, Andi Lukman Hakim Maria Paristiowati Marwan Marwan Maulana, Aga Maulydia, Nur Balqis Maysarah, Hilda Medyan Riza Mirda, Erisna Mirja, Mirja Misbullah, Alim Muhammad Adam, Muhammad Muhammad Ichsan Muhammad Ichsan Muhammad Sabri Muhammad Subianto Muhammad Yanis Muhammad Yusuf Mukhlisuddin Ilyas Muliadi Ramli Muslem Muslem, Muslem Musvira, Intan Natasya Natasya Nizamuddin Nizamuddin Nova Yanti Pasyamei Rembune Kala Patwekar, Mohsina Prasetio, Rasi Purnama, M. Risky Putri Raisah Raisah, Putri Raudhatul Jannah Razief Perucha Fauzie Afidh Rinaldi Idroes Rizkia, Tatsa Sasmita, Novi Reandy Shofi, Shofi Siti Maulina Rukmana Souvia Rahimah Suhendra , Rivansyah Suhendra, Rivansyah Suhendrayatna Suhendrayatna Surna, Muhammad Ipan Susanna Susanna Syamsiar, Syamsiar Taufiq Karma Teuku Rizky Noviandy Teuku Zulfikar Tjut Chamzurni TRINA EKAWATI TALLEI Wahyuni, Srie Wangi, Putri Ayu Sekar Wildan Seni, Wildan Wiranatakusuma, Dimas Bagus Wiwik Handayani Yustiana Yustiana, Yustiana Zahriah, Zahriah Zuchra Helwani, Zuchra Zulkarnain Jalil