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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 5 Documents
 1 
Search results for , issue "Vol. 1 No. 1 (2023): July 2023" : 5 Documents clear
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.

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