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Aceh International Journal of Science and Technology
Published by Universitas Syiah Kuala
ISSN : 20889860     EISSN : 25032348     DOI : http://10.13170/aijst
Core Subject : Science, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences
Aceh International Journal of Science & Technology (AIJST) is published by the Graduate School of Syiah Kuala University (PPs Unsyiah) and the Indonesian Soil Science Association (Himpunan Ilmu Tanah Indonesia, Komda Aceh). It is devoted to identifying, mapping, understanding, and interpreting new trends and patterns in science & technology development, especially within Asian countries as well as other parts of the world. The journal endeavors to highlight science & technology development from different perspectives. The aim is to promote broader dissemination of the results of scholarly endeavors into a broader subject of knowledge and practices and to establish effective communication among academic and research institutions, policymakers, government agencies, and persons concerned with the complex issue of science & technology development. The Journal is a peer-reviewed journal. The acceptance decision is made based upon an independent review process supported by rigorous processes and provides constructive and prompt evaluations of submitted manuscripts, ensuring that only intellectual and scholarly work of the greatest contribution and highest significance is published. The AIJST publishes original conceptual and research papers, review papers, technical reports, case studies, management reports, book reviews, research notes, and commentaries. It will occasionally come out with special issues devoted to important topics concerning science & technology development issues. Scopes Starting in 2016, AIJST has focused on science and engineering aspects, and therefore now AIJST considers the topics but not limited to : Engineering (Mechanical, Chemical, Civil, Transportation) Geology and Geomorphology Environmental Science (Hydrology, Pollution, Water Treatment, Soil Science, Climatology) Physical Oceanography Mathematics Physics and Geophysics Geospatial and Information Technology
Arjuna Subject : Ilmu Lingkungan (semua ketegori) - Global dan Perubahan Planet
Articles 354 Documents
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Utilization of Coal-Mining Mud as a Safe and Environmentally Friendly Building Material Alam, Pocut Nurul; Yulianis, Yulianis; Hadif, Fauzil; Kurniawan, Reinaldy; Aslam, Izzan Nur
Aceh International Journal of Science and Technology Vol 13, No 1 (2024): April 2024
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.13.1.37303

Abstract

Coal-mining mud is one of the wastes that must be treated before being discharged into the environment. The mud contains a lot of heavy metals which have the potential to pollute the environment and endanger human health. On the other hand, the metal contents in the mud can be used as components to strengthen building materials such as brick. In this study, an investigation was carried out to check whether the risk of heavy metal contamination in the coal-mining mud can be minimized when the brick is produced. In addition, this study also tested whether the bricks produced from the utilization of the mud were strong enough to be used as construction materials. The results obtained indicate that metal contamination can be significantly minimized through the solidification process of brick products and is following the Indonesian national quality standards. This study also shows that even though the bricks meet the strength standard for the certain purpose applied in Indonesia, the utilization of coal-mining mud mixed with cement and sand was not sufficient to produce strong bricks even though the weight obtained was quite light.
Drying Characteristics of Cacao Beans using Modified Solar Tunnel Dryer Type Hohenheim Khathir*, Rita; Kurniawan, Edi; Yunita, Yunita; Syafriandi, Syafriandi
Aceh International Journal of Science and Technology Vol 12, No 3 (2023): December 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.3.30246

Abstract

Drying cacao has been conducted by open-sun drying systems by farmers worldwide. To improve the cacao drying, the use of solar dryers can be applied. The objective of this study was to evaluate the drying characteristics of using a modified solar tunnel dryer type Hohenheim in drying cacao. As a comparison, the sun-drying method was also conducted. The parameters observed were temperature, relative humidity (RH), weight loss, moisture content, fat content, hardness, and drying rate. Results showed that the average temperature of the Hohenheim dryer was higher at about 10C than the ambient temperature. However, the Hohenheim dryer's drying temperature fluctuated due to the oscillation of solar irradiation. The drying process took time for 12h in 2 days. The humidity in the drying chamber was high, above 50%, representing that the dryer needed additional fans to improve its air circulation. The final moisture content of cacao dried using Hohenheim dryer and sun-drying was 12.7 and 17.4%, respectively. The drying rate of cacao dried using a Hohenheim dryer was double that of sun-drying. Therefore, the dryer can speed up the drying time and protect the cacao from contamination.
Combined Effect of Low and High Rate of Corrugated Steel Fiber and Stirrups on Mechanical Performance of SFSCC Beams Chaib*, Sihem; Lassoued, Rachid
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.19723

Abstract

To improve the fragile nature of concrete, its low tensile strength, and a view to giving it the desired properties, which serve to build more durable structures at less cost, the association of a self-consolidating concrete with fiber, is considered a wise combination. However, given the limited amount of research on the response of SFSCC structures, designers and engineers do not use this material with confidence. In the present work, an experimental companion was conducted to examine the combined effect of fibers and stirrups, including the low and high rate of steel fiber, on the behavior of SFSCC beams. This choice allowed working on economically viable SFSCC. Beams were also madewith ordinary concrete and others with self-consolidating. Thirty-six beams were of identical cross-section 10x20cm and length of 120cm; carried out with or without longitudinal and transverse reinforcement. Before proceeding with the main part of the research program, the concrete mixtures were characterized first in the fresh state by the following tests: Slump Flow, Time Flow T500; J-Ring, L-Box, V-Funnel, and Sieve stability, and then in the hardened state: compressive and tensile strengths. In the light of the results obtained, it was found that adding steel fibers to fresh self-consolidating concrete decreased its workability and fluidity but improved its hardening properties. Subsequently, the addition of the steel fibers increased the flexural capacity of the beams significantly and enhanced their ductility. Also, an addition of the steel fibers in an adequate percentage, in this case at 0.90%, made it possible to replace the shear reinforcements and can lead to changing the mode of failure from a collapse by brittle shear to a mechanism of ruin in ductile bending.
Geochemical Analysis of Calcareous Shale of Baong Formation (North Sumatera Basin) as Potential Source Rock Putra, Hidayat Syah; Alfian, Zika; Sartika, Dewi; Rifqan, Rifqan; Muhni, Akmal; Adrian, Fahri
Aceh International Journal of Science and Technology Vol 13, No 1 (2024): April 2024
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.13.1.36962

Abstract

This research is related to calcareous shale whose samples were obtained from surface data (outcrop). This rock outcrop is characterized as a rock rich in organic material and impermeable, so it is predicted to become a source rock of oil and gas petroleum system. The amount of organic content or carbon material and the level of maturity of the rock is a benchmark for determining whether or not it is appropriate to be called a source rock of the petroleum system in the North Sumatra Basin (NSB) area. The method used in the present study is the rock-eval pyrolysis method and the determination of Total Organic Carbon is carried out through laboratory testing. Based on the results of Rock-Eval Pyrolysis testing, the maturity level or Tmax of the rock is 446-degree Celsius which indicates the peak mature category with kerogen type in the form of II/III which tends to produce oil and gas prone. The results of the Total Organic Carbon (TOC) test show a value of 1.26% which is included in the category of organic matter richness in the good category. Based on the results of these two tests, it can be concluded that the Calcareous shale found in the North Sumatra Basin (NSB) can be categorized as a good Source Rock with a Peak Mature maturity level and has the potential to produce Oil and Gas (Mixed oil and gases).
The Effect of Low-Density Poly Ethylene (LDPE) Towards Plastic Oil Quality Hariadi, Dedy; M. Saleh*, Sofyan; Yamin, R. Anwar; Aprilia, Sri
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.17967

Abstract

Nowadays, the use of plastics is inseparable from daily life activities for both industrial commercial and household needs. Every year, an average individual consumes 700 plastic bags. Furthermore, the major types of plastic pollutants are High Density Polyethylene (HDPE) and Low Density Polyethylene (LDPE). The nature of LDPE plastic makes it very difficult to undergo decomposition. Subsequently, efforts to overcome this problem have been carried out by several methods of processing or utilizing its waste through pyrolysis. This s tudy aims to determine the effect of the quality of LDPE plastic waste on the plastic oil produced from the pyrolysis process. Based on their chemical compounds, all plastic oils produced were categorized as carbon compounds instead of hydrocarbons. Althou gh, from the quality of the LDPE plastic used, the process produced gasoline, naphtha, and kerosene, the quality of each oil was different. Therefore, the higher the quality of the LDPE plastic used, the better the quality of the oil produced.
Probabilistic Forecasting of Energy Consumption using Bayesian Dynamic Linear Models Aulia, Hartika; Syaharuddin, Syaharuddin; Mandailina, Vera; Gervas, Hamenyimana Emanuel; Ashraf, Hameed
Aceh International Journal of Science and Technology Vol 13, No 1 (2024): April 2024
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.13.1.38291

Abstract

This study aims to conduct a systematic literature review on the development of mathematical models for forecasting energy consumption using a probabilistic approach, particularly focusing on the Bayesian Dynamic Linear Model (BDLM). The research method employed is Systematic Literature Review (SLR), utilizing literature sources indexed in Scopus, DOAJ, and Google Scholar, with publication dates ranging from 2014 to 2024. The findings of the research indicate that the application of BDLM has made a significant contribution to the optimization of energy management, especially in sectors such as industry and commercial buildings. The study highlights the effectiveness of BDLM in accurately predicting energy consumption through a probabilistic approach that efficiently manages uncertainty. However, the research also emphasizes that BDLM presents limitations and challenges that warrant attention, including the complexity involved in parameter determination and model validation processes, as well as the importance of addressing potential biases and considering factors such as deployment impacts. This research provides deep insights into the potential and challenges in the development of mathematical models for forecasting energy consumption, while also offering directions for further research in this field.
Tuberculosis Detection using Gray Level Co-Occurrence Matrix (GLCM) and K-Nearest Neighbor (K-NN) Algorithms Anwar, Fuad; Yunianto*, Mohtar; Putri, Rahmanisya Fani Aisha
Aceh International Journal of Science and Technology Vol 12, No 3 (2023): December 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.3.33241

Abstract

Research has been conducted on detecting tuberculosis (TB) using machine learning. In this study, chest Xray (CXR) image data was used with a pixel value of 512 x 512 and PNG format consisting of normal lung images and TBinfected lung images in a 50:50 ratio; the number of images was 200 training data images and 80 testing data images. In the preprocessing stage, grayscaling is carried out so the image has a grayscale. Then, do the image improvement using contrast stretching. Furthermore, image extraction was carried out using 22 GLCM features with variations in the direction of the angles of 0, 45, 90, and 135. The result of feature extraction data is then identified using KNN Classification. The training results have the highest accuracy value with variations in the direction of the GLCM angle of 45 and the value of K = 3; at the testing stage, it produces an accuracy of 90%.
Utilization of Acoustic Wave Velocity for Permeability Estimation in Static Reservoir Modeling: A Field Case Prakoso*, Suryo; Burhannudinnur, Muhammad; Irano, Teddy; Herdiansyah, Firman
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.20328

Abstract

Several researches have shown that P-wave velocity carries information on the complexity of the rock's pore geometry and pore structure. Their complexity can be characterized by critical porosity. Therefore, the P-wave velocity is used to estimate permeability. This research uses data taken from the Tomori formation from Banggai-Sula basin, Central Sulawesi, which is a carbonate rock reservoir. Also, this research aims to obtain a 3D permeability model by using acoustic wave velocity cube data. The results show that permeability can be modeled well using acoustic wave velocity data. Furthermore, compared to the raw data log of permeability, the modeling results using wave velocity based on critical porosity show good results. This method is another alternative to permeability modeling if acoustic wave velocity cube data is available.
Comparing Nanofiltration and Ion Exchange for Reverse Osmosis Pretreatment in Industrial Water Treatment: A Techno-Economic Analysis Harwin, Harwin
Aceh International Journal of Science and Technology Vol 13, No 1 (2024): April 2024
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.13.1.37113

Abstract

Water softening is a crucial process in various industrial applications, and the selection of an appropriate system involves balancing technical efficiency, environmental impact, and economic considerations. This paper presents a comprehensive analysis of two prominent industrial water softening systems, Nanofiltration (NF) and Ion Exchanger (IX), through a multidimensional lens. The systems design and sizing were simulated with computer assistance, using the DuPonts WAVE Water Treatment Design Software version 1.82. The technical evaluation, based on simulations, revealed that IX outperformed NF in total hardness removal ( 99%) at the expense of a slight increase in Total Dissolved Solids (TDS). In contrast, NF demonstrated a superior ability to reduce TDS, albeit with lesser total hardness removal. Environmental considerations highlighted trade-offs, with NF generating higher wastewater volumes and IX producing wastewater with highly concentrated TDS, necessitating complex treatment processes. Economically, NF generally incurred higher Total Annual Costs (TAC) at lower total hardness concentrations, while IX became costlier at higher concentrations. A selection chart is introduced to aid decision-making based on economic considerations. This research offers valuable insights for industries seeking an optimal water softening solution, balancing technical efficiency, environmental impact, and economic considerations. The findings provide a nuanced understanding to guide system selection based on specific water quality requirements and economic constraints.
The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data Saroji*, Sudarmaji; Winata, Ekrar; Hidayat, Putra Pratama Wahyu; Prakoso, Suryo; Herdiansyah, Firman
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.18749

Abstract

Lithofacies classification is a process to identify rock lithology by indirect measurements. Usually, the classification is processed manually by an experienced geoscientist. This research presents an automated lithofacies classification using a machine learning method to increase computational power in shortening the lithofacies classification process's time consumption. The support vector machine (SVM) algorithm has been applied successfully to the Damar field, Indonesia. The machine learning input is various well-log data sets, e.g., gamma-ray, density, resistivity, neutron porosity, and effective porosity. Machine learning can classify seven lithofacies and depositional environments, including channel, bar sand, beach sand, carbonate, volcanic, and shale. The classification accuracy in the verification phase with trained lithofacies class data reached more than 90%, while the accuracy in the validation phase with beyond trained data reached 65%. The classified lithofacies then can be used as the input for describing lateral and vertical rock distribution patterns.

Page 29 of 36 | Total Record : 354

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