Aceh International Journal of Science and Technology
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The Influence of Cooling Techniques on The Performance of Pack Carburized Low Carbon Steel Using Cypress Charcoal
Full text linkThis study investigated the impact of different cooling media on low-carbon steel's hardness and wear characteristics after pack carburizing using cypress charcoal. This research method involves conducting an experimental process known as pack carburizing. It utilizes cypress charcoal as an energizer and sodium carbonate as a catalyst for heat treatment. The cypress charcoal and sodium carbonate volume comprise 90% ACR and 10% NaCO3. The mixture is heated in a furnace at a temperature of 925 C for 3 hours and then cooled using different media, including air, SAE 20 oil, salt water, and water. Material testing uses mechanical tests, specifically hardness and wear tests. According to the study findings, the hardness value exhibited a noticeable rise, reaching a peak of 277.694 HV in the air-cooling medium. In contrast, the lowest value of 198.417 HV was observed in the same medium. In addition, the wear rate is affected by the cooling medium. The wear rate is highest at 0.0657 grams/sec in air cooling media, while it is lowest at 0.0347 grams/sec in air cooling media. This indicates that the hardness value and wear rate value are inversely related. In other words, materials with higher hardness have smaller wear rates, and vice versa. The variation in cooling rates is primarily due to the differences in viscosity among the cooling mediums
Fusing Self-Regulated Learning and Machine Learning to Enhance Open and Distance eLearning Systems. A systematic review
No full textThere are rapid advancements in the use of digital technologies in Open and Distance eLearning (ODeL) environments worldwide. Digital technologies have significantly enhanced Open and Distance eLearning by improving accessibility, flexibility, and the quality of education. Learners from remote and underserved areas can access educational resources anytime, thereby supporting inclusive education for everyone, regardless of their diverse needs. However, most ODeL systems face challenges such as high student dropouts, low retention rates, and lack of instant instructional and user support. These challenges have given birth to the need for innovative approaches that will enable learner autonomy, motivation, and personalized support. One strategy that ODeL institutions can employ involves combining Self-Regulated Learning (SRL) and Machine Learning (ML) techniques to create intelligent and adaptive learning environments. SRL is very important in ODeL because it allows learners to have control of their own learning by setting metacognitive strategies such as goal setting, strategic planning, self-monitoring, and self-evaluation. The purpose of this systematic review was to explore the extent to which SRL and ML have been fused to enhance teaching and learning in ODeL contexts. Using a systematic literature review methodology, the study utilized 39 peer-reviewed articles published between 2019 and 2025, drawing on major academic databases, including Google Scholar, SpringerLink, ScienceDirect, IEEE Xplore, and Scopus. This study focused on reviewing studies that implemented ML techniques to model, support, or enhance SRL strategies in ODeL digital learning platforms. Findings from the study indicated that a huge number of studies utilise ML algorithms such as reinforcement learning, natural language processing, supervised learning, and unsupervised clustering in analysing learners data and provide adaptive feedback and recommendations that are related to SRL theory. While several studies highlight the effectiveness of ML in enhancing SRL, most are found within structured online courses or intelligent tutoring systems, rather than fully in open or distance learning environments. Furthermore, there is limited research that has focused on the development of ODeL systems that utilise both SRL and Machine Learning to enhance teaching and learning. This research study concluded by giving coding ideas on how ML and SRL can be combined to enable ODeL institutions to develop Learning Management Systems (LMS) that improve learner engagement, retention, and performance
Comparison of the Accuracy of the Levenberg-Marquardt and Trust-Region Methods in Solving Multivariable Non-Linear Equation Systems
No full textMultivariable nonlinear equation systems are commonly found in various disciplines such as engineering, physics, economics, and artificial intelligence. Analytical solutions are often difficult to obtain, necessitating the use of numerical approaches. This study aims to evaluate and compare the performance of the Levenberg-Marquardt and Trust-Region methods in solving multivariable nonlinear equation systems. Computational simulations were performed using MATLAB software with an error tolerance of 0.001 and a maximum iteration limit of 100. The test system involved a combination of trigonometric, exponential, and polynomial functions to ensure computational complexity. The study's results show that both methods are capable of achieving solutions with high accuracy. The Levenberg-Marquardt method demonstrated higher efficiency, achieving convergence in only 2 iterations with a final error of 1.866 10. In contrast, the Trust-Region method required 27 iterations but yielded a smaller error of 4.768 10. Three-dimensional visualization revealed that the solution was obtained from the intersection point of the three function surfaces. These findings confirm that the selection of numerical methods should consider the priority between iteration efficiency and solution accuracy. The contribution of this research lies in presenting a comparison of the performance of two popular algorithms with controlled simulation parameters, which can serve as a basis for the development of numerical methods in larger dimensional system
Improved Performance on Inverted V Eccentrically Braced Frames (EBF) by Implementing Shear Link and Installing Web Stiffener in Link
Full text linkEccentrically Braced Frame (EBF) is a structural system that is advised to be built in seismically active areas since they are characterized by good stiffness and ductility. A large and stable hysteretic curve, which corresponds to good seismic performance, is produced by the combination of improved stiffness and ductility in EBF. The diagonal component of EBF, known as a brace, contributes to its stiffness. Meanwhile, the short beam, also known as the link element, provides ductility in EBF. One element that is essential as an energy dissipator in EBF is a link element. By displaying a sizable and steady hysteretic curve, a prior study found that EBF with a flexural link could effectively dissipate the seismic energy. But to achieve a higher EBF, the seismic performance still needs to be enhanced. An analysis of various EBF models in Inverted V configurations was conducted in this paper. Each model was prepared with different shear link characteristics. Installing web stiffeners in the link to improve its seismic performance was also taken into consideration in this study. To obtain seismic performance, the cyclic loads were employed to each model under conditions of yield displacement control. Analysis of the data resulted in the load-displacement hysteretic curve. Next, using the hysteretic curve, the three seismic performance parameters, i.e., strength, stiffness, and dissipation energy were further developed. The investigation showed that compared to earlier studies, the EBF with shear links showed a bigger and more stable hysteretic curve which means better dissipated energy. Additionally, adding web stiffeners significantly increases the EBF's seismic capability. Therefore, because of the improved seismic characteristics, it is advised to establish the EBF using a shear link reinforced by web stiffeners in an earthquake-hazard area
Analysis of Illegal Gold Mining (PETI) Impact on The Environment with TDS, TSS, Mercury and Cyanide Parameters in Water and Sediment of Cikaniki River
Full text linkGold production from artisanal mining extraction reaches 120 tons annually, providing significant environmental and economic impacts for the community. The processing method used triggers environmental pollution, because it produces tailings in the form of metal mercury and cyanide. This research was conducted at the location of post Illegal gold mining (PETI), although PETI activities have been disciplined, but based on the characteristics of mercury which is difficult to dissolve in water, easily binds to suspended solids and easily deposited to the bottom of the waters, can pollute river sediments. The purpose of the study was to determine the levels of Total Dissolved Solid (TDS), Total Suspended Solid (TSS), mercury and cyanide in the Cikaniki River Watershed, based on Government Regulation No. 22 of 2021. The purposive sampling method was used in determining the sampling location at 3 observation stations for surface water and sediment, namely station 1 area where is former gold processing. Station 2 river body where former PETI produces mercury waste, station 3 is a place where there is no gold processing. TDS and TSS measurements using the gravimetric method, mercury and cyanide levels using ICP-OES. The results of laboratory sediment analysis of 3 observation location in Cisarua Village, Curug Bitung Village, and Lukut Village, for the TDS and TSS parameters, mercury was detected at the highest level at point 3 in Lukut Village. Luku Village is the most downstream location of the Cikaniki River which is located very far form the peoples gold processing site. This concludes that after PETI activities occur, the distribution of mercury (Hg) waste spread to the most downstream areas of the Cikaniki River is always present even though its presence is still below environmental quality standards
Petrology and Geochemistry of Igneous Rocks in Gunung Badak Complex, Ciletuh Palabuhanratu Geopark, Sukabumi, West Java
Full text linkGunung Badak Complex is located in Ciletuh Palabuhanratu UNESCO Global Geopark, which preserves significant records of tectonic evolution in Southern West Java. This research aims to characterize igneous rocks and interpret tectonic implications. The methodology includes petrographic analysis, major element geochemical characterization using X-Ray Fluorescence (XRF), and trace elements and Rare Earth Element (REE) analysis using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) from 8 selected samples. The results identify three distinct rock groups consisting of diorite (SiO 51.5-52.48%), basalt (SiO 50.69-52.52%), and serpentinized peridotite (SiO 40.59%, MgO 34.63%). Diorite and basalt exhibit tholeiitic affinity with low KO (0.25-0.69%), Mg# 49.67-58.13, indicating early-stage island arc magmatism. Serpentinized peridotite exhibits residual harzburgite characteristics with Mg# 89.29. Trace element geochemistry shows enrichment of LILE (Cs, Ba, Pb, Sr) relative to HFSE (Nb, Zr), with negative Nb-Ta anomalies and La/Nb ratios of 2.21-3.75 typical of subduction environments. Diorite-basalt displays moderate LREE enrichment ((La/Yb)N 1.40-2.63), while serpentinized peridotite shows LREE depletion ((La/Yb)N 0.54). Dy/Yb ratios (1.20-1.91) indicate magma sources from partial melting of spinel peridotite at depths 50 km. The geodynamic model indicates that serpentinized peridotite originated from lithospheric mantle in a supra-subduction zone (SSZ) environment during Eocene subduction initiation, while diorite and basalt formed during early Miocene island arc magmatism (~22 Ma)
Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection
Full text linkDeep Learning (DL) and Support Vector Machine (SVM) was used for a plethora number of researches lately. Deep Learning works by representing data in layers of learning layers so that the representation becomes more meaningful, and Support Vector Machine tries to find the hyperplane that maximizes the margin between the hyperplane and the closest data points from each class so that the classification becomes more accurate. Both algorithms have proven to be powerful tools for any classification problem specially to classify or identify image patterns. However, the performance of machine learning algorithms can be affected by any factor, thus sometimes we found several algorithms that are generally known to be powerful, even showing unsatisfactory results. The purpose of this study is to compare the ability of classification methods Deep Learning and Support Vector Machine to detect face mask. Face mask detection has gained significant attention and importance in the context of public health and safety, particularly during the COVID-19 pandemic. The study revealed that Deep Learning algorithm performed better than the Support Vector Machine Algorithm and showed excellent performance in all four metrics. In particular, the Deep Learning algorithm achieved an average Sensitivity/Recall rate of 92%, a Specificity rate of 95.44%, a Precision rate of 95.28%, and an Accuracy rate of 93.72%
Utilization of IoT Technology in Modernization of Transportation Infrastructure: Conceptual and Implementation Review
No full textThe development of intelligent transportation infrastructure is increasingly supported by the Internet of Things (IoT), offering opportunities to improve data-driven mobility management through real-time sensing and automation. This study aims to examine the conceptual foundations and practical implementations of IoT-based systems in the modernization of transport infrastructure, emphasizing architectural design, communication protocols, and deployment challenges. The methodology combines a literature-based synthesis with a simulation experiment using Node MCU ESP8266 microcontrollers, MQTT (Message Queuing Telemetry Transport) communication, Node-RED gateway integration, and cloud dashboard visualization. A total of 22 relevant scientific studies were reviewed, and six real-world case studies were evaluated to extract recurring design patterns and bottlenecks. Simulation results demonstrate that the proposed System maintains a low average transmission delay (128 ms) and minimal packet loss (0.83%) over 720 data cycles, indicating technical feasibility for small-to-medium scale deployments. The evaluation further identifies three critical factors affecting IoT transport systems: network reliability, cloud integration, and scalability. While MQTT over TLS and modular software frameworks enhance real-time performance and system resilience, network instability, particularly in rural or outdoor settings, remains a significant constraint. The study concludes that a scalable and sustainable IoT-based transportation infrastructure requires a context-aware, modular, and multi-layered architecture that is adapted to local operational conditions. The proposed framework provides practical guidance for developers, urban planners, and policymakers seeking to transition from conceptual models to real-world, innovative mobility applications
Geochemical Analysis of Calcareous Shale of Baong Formation (North Sumatera Basin) as Potential Source Rock
Full text linkThis 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)
Long-term Monitoring of Low-cost Seismometers: Consistency Analysis of The Instrument
Full text linkInstruments have become an essential part of conducting a study or research. With the aid of instruments, the measurement process can be faster, more efficient, and more accurate. However, an instrument also has a limited service life. Over time, the performance of the instrument will degrade. Therefore, the equipment must be regularly maintained and calibrated periodically. This research aims to test the measurement consistency of a low-cost seismometer (RS-3D). The approach involves long-term measurements to assess the instrument's stability in taking measurements. The measurement data is then processed and presented as frequencies using spectrum analysis. The research findings indicate that the instrument's consistency is generally good, with an average standard deviation of 0.18 and a coefficient of variation of 5%. Additionally, 95% confidence interval calculations yielded values of 2.520.02 for measurements at RKD, 3.040.05 for measurements at GLT-USK, and 3.30.04 for measurements at GFT-USK. Data validation was performed using the equations from building codes, showing that the difference between the measured microtremor frequency and the empirical equation was less than 1, indicating good measurement results. The conclusion drawn from this study is that a higher standard deviation value indicates a more distributed data spread, signifying less consistent research data. Conversely, a lower standard deviation indicates that the data is more concentrated around the mean value, indicating more consistent measurement results. Moreover, with previous studies having conducted validation and consistency testing, it is hoped that both tests will be routinely performed during instrument maintenance