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Leuser Journal of Environmental Studies
Published by PT. Heca Sentra Analitika
ISSN : -     EISSN : 29887038     DOI : https://doi.org/10.60084/ljes
Core Subject : Science, Education, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Energy Environmental Science Other
Leuser Journal of Environmental Studies is a distinguished international, peer-reviewed scientific journal dedicated to advancing knowledge in the field of environmental studies. LJES aims to provide a platform for researchers, practitioners, and academics to publish their high-quality original research articles, review articles, and case reports related to various aspects of the environment. The journal overarching goal is to foster interdisciplinary research that connects scientific and technological advancements to real-world applications, with a specific emphasis on the impact they have on society and the environment. The scope of LJES encompasses a wide range of topics within the field of environmental studies, including but not limited to: environmental science, biodiversity and conservation, climate change and sustainability, environmental policy and governance, environmental impact assessment, pollution and remediation, environmental health, ecological modeling, sustainable resource management, environmental education and communication
Arjuna Subject : Ilmu Lingkungan (semua ketegori) - Ilmu Lingkungan (Lain-Lain)
Articles 26 Documents
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Design Concept of Information Control Systems for Green Manufacturing Industries with IoT-Based Energy Efficiency and Productivity Yandri, Erkata; Idroes, Rinaldi; Maulana, Aga; Zahriah, Zahriah
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.v1i1.36

Abstract

In today's and future industrial competition, IoT and the Fourth Industrial Revolution are unavoidable. Indonesia must be prepared to compete globally in an increasingly efficient and integrated industry, including efficient energy use and renewable energy. This issue has received little strategic and scientific thought, particularly in Indonesia. This study purposes to create a conceptual model of an information control system in the industry, which will include operational performance. The method involves four steps. Firstly, the process flow within the industry is comprehensively analyzed, including the input, process, and output (IPO) aspects. Secondly, all information pertaining to each production process is integrated into the information system. Thirdly, a management control system (MCS) is proposed, incorporating key performance indicators (KPIs), allowing real-time monitoring by management. Lastly, real-time information data on resource sharing is submitted to the information sharing control system within similar industrial clusters. This enables related business parties to optimize their resource utilization based on the provided information. The results show that green manufacturing can be initiated by controlling energy-saving and productivity-related KPIs. The concept of IoT green manufacturing depends on active involvement from the government, industry and the public. A crucial aspect of this system is how the industry effectively manages production performance through shop floor control (SFC).
Method Validation for Pesticide Residues on Rice Grain in Aceh Besar District, Indonesia Using Gas Chromatography-Electron Capture Detector (GC-ECD) Winarsih, Agus; Idroes, Rinaldi; Zulfiani, Utari; Yusuf, Muhammad; Mahmudi, Mahmudi; Saiful, Saiful; Rahman, Sunarti Abd
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.v1i1.37

Abstract

Analysis of pesticide residues in rice in Aceh Besar District using the Gas Chromatography – Electron Capture Detector (GC-ECD) method has been carried out. This study aims to validate the analytical method and determine the pesticide residue levels of Dichlorvos, Dimethoate, Bifenthrin, and λ-Cyhalothrin in rice samples. Rice samples in branded rice were taken from the Districts of Want Jaya, Indrapuri, Darussalam, Suka Makmur, Simpang Tiga, Kuta Baro, and ground using a grinder. The powder sample was extracted by the QuEChERS method and analyzed by GC-ECD. The results of the linearity test have met the requirements with the coefficient of determination (R2), which is an average of 0.98. The LOD values ranged from 0.013 to 0.017 mg/kg, while the LOQ ranged from 0.022 to 0.079 mg/kg. The results of precision and reproducibility (% RSD, n = 6) show the values of 0.56 - 1.26% and 1.14 - 2.19%, respectively, and the accuracy value (%Recovery) shows the results of 99.71 - 101.84%, with an RSD value of 2.42 - 3.59%, meet the requirement of 20%. The results of the analysis of the sample showed that sample A had a large %Recovery value in the Dichlorvos analyte, namely 139.10%, with the calculation that the Dichlorvos analyte contained 0.0206 mg/Kg. This value has not passed the MLR set by the European Food Safety Authority, which is 0.2 mg/Kg. In the other rice samples, no pesticide residue analytes were detected. The calculation of %Recovery of each analyte in the spiked sample ranged from 80-101%, which indicated that the pesticide residue analysis carried out had good accuracy, namely the requirement of 70-120%.
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.
Utilization of Empty Palm Fruit Bunches as a Carbon Source for Cellulase Production to Reduce Solid Waste from Palm Oil Amraini, Said Zul; Nazaris, Nazsha Nayyazsha; Andrio, David; Mardhiansyah, Muhammad; Helwani, Zuchra
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.v1i1.41

Abstract

Cellulase enzymes are widely used in textile, food, detergent, pulp and paper industries and biofuel, so the need for enzymes continues to increase every year. One of many biomass wastes found in Indonesia is empty fruit bunches (EFB) that can be used as a carbon source as a substitute for expensive pure cellulose (CMC) and Bacillus subtilis isolates. This study aims to obtain the optimum conditions the production of cellulase enzymes with variations in the pre-treatment of EFB and pH variations of the medium using Bacillus subtilis. Pre-treatment was carried out to hydrolysed lignocellulosic biomass was more easily and increased glucose levels which would enter the next production stage. Variations in pre-treatment were carried out by adding acids, bases and organosolv process, as well as variations in pH at 6.5; 7.0 and 7.5, respectively. Enzyme activity was calculated using the Nelson-Somogyi method. When using acid, the enzyme activity is 0.041, while using organosolv, it is obtained 0.057 each at pH 7. The results showed that the highest enzyme activity was obtained at a pH of 7.0 and a temperature of 40 ºC on EFB substrate pretreated with a base of 0.204 U/ml. These findings emphasize the potential benefits of using EFB waste as a substrate for cellulase enzyme production, by providing an alternative approach to decrease raw material expenses and mitigate environmental pollution.
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.
The Effect of Life History on Alopias pelagicus Overexploitation Vulnerability: A Literature Review Hewindati, Yuni Tri; Novita Sari, Dhian
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.v1i2.54

Abstract

Alopias pelagicus Nakamura 1935 or pelagic thresher shark is an epipelagic species of shark prone to overexploitation due to its epipelagic habitat and slow life history. In 2019, based on existing data on abundance and exploitation, A. Pelagicus was included in the International Union for Conservation of Nature (IUCN) Red List of Threatened Species with the category of endangered (EN). This literature review analyzed the relationship between A. pelagicus life history and overexploitation susceptibility. The method used is a comprehensive search of international journals in online databases from ScienceDirect and Google Scholar with certain inclusion and exclusion criteria. Based on the criteria, seven out of 270 search results of international journal articles were included for the analysis. The results from the seven journal articles shows that A. pelagicus has a slow life history or k-selected life history. This life history is characterized by slow sexual maturity, low fecundity, long gestation period, annual reproductive cycle, slow growth, long lifespan, and low natural mortality rate. This life history makes A. pelagicus prone to overexploitation because if the mortality rate of catching exceeds the natural mortality rate, it will take a long time for A. pelagicus to return to their original population size.
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.
Utilizing Bentonite as a Natural Material to Enhance the Quality of Community Water Resources in the Urban Area Ulhaq, Muhammad Zia; Hanan, Dafif; Salsabila, Athaya; Lala, Andi; Muslem, Muslem; Akbar, Zulhiddin; Zahriah, Zahriah
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.v1i2.94

Abstract

In this study, the researchers investigated the state of water sources and the potential of bentonite as a water treatment agent. The study encompassed measurements of key water quality parameters for river and well water sources, including pH, TDS, conductivity, and salinity. The findings revealed that while pH levels were generally within the clean water standards, TDS values exceeded the threshold, particularly in river water samples. This suggests contamination due to urban activities and rising sea levels. Furthermore, the study explored using both activated and non-activated bentonite as an adsorption agent to remove contaminants from water sources. The results indicated that bentonite effectively increased pH levels, especially in well water samples, and significantly reduced TDS, conductivity, and salinity values, with non-activated bentonite being a preferred option for river water treatment and activated bentonite for well water treatment. These findings emphasize the potential of bentonite as a valuable water treatment solution. The specific characteristics of the water source should guide the choice between activated and non-activated bentonite. This tailored approach can lead to more effective and sustainable water treatment, contributing to improved water quality and availability for the community in the coastal region.
Biocomposite Innovation: Assessing Tensile and Flexural Performance with Maleated Natural Rubber Additives Fatra, Warman; Anuar, Kaspul; Oktriyono, Febri Dwi; Fernando, Rivo; Helwani, Zuchra; Rusyana, Asep; Zul Amraini, Said
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.v1i2.98

Abstract

Fiberglass is the most common reinforcing fiber used in composites, with polymer matrices having high tensile strength and chemical resistance, including an excellent insulating property; however, they are non-degradable. Natural fiber reinforced polymer composites have advantageous properties such as lower density and price, when compared to synthetic composite products. In addition, hybrid composites may be obtained depending on various properties such as the fibers' length, structure, content and orientation, matrix bonding and arrangement. This study was carried out to determine the effect of adding Maleated Natural Rubber (MNR) from natural rubber as a coupling agent, in order to produce the highest tensile and flexural strength. The hand lay-up and vacuum bag methods with the Response Surface Method-Central Composite Design (RSM). -CCD) were used. The composite arrangement pattern was E-glass/OPEFB/E-glass, the volume fraction of OPEFB (oil palm empty fruit bunches):E-glass was 40:60, 50:50 and 60:40, the fraction volume of OPEFB + E-glass:matrix was 40:60, 50: 50, 60: 40 and the coupling agent were added by 9, 10 and 11% of the total epoxy resin used. Furthermore, the composite mold was made of glass with dimensions of 200mm x 50mm x 50mm. The results showed that the composite product obtained from both methods had a tensile strength value, which was influenced by the variable OPEFB fiber and epoxy resin. Meanwhile, the flexural strength was influenced by the OPEFB fiber and the quadratic factor of the epoxy-MNR resin.
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.

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