Aceh International Journal of Science and Technology
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Optimization of Injection Moulding Parameters for Constructing Motorcycle Footstep Cover Using an Environmentally friendly Composite
Full text linkAgra-forestry waste and recycled polypropylene have been combined to create sustainable composite materials for use in automotive applications in response to increased environmental concern over the depletion of petroleum-based resources. In this study, an injection molded motorcycle footstep cover was manufactured from recycled polypropylene (rPP) composite reinforced with ironwood powder. It aims to optimize the manufacturing process parameters of barrel temperature, mould temperature, and holding time in minimizing shrinkage and maximizing product weight. This current research employed the Taguchi L4 orthogonal array experimental design followed by the multi-objective grey relation analysis (GRA). In this study, the composite material consisted of 30% ironwood powder, 65% r-PP, and 5% coupling agent. The specimens were processed using injection molding with two different levels for each parameter of barrel temperature, moulding temperature, and holding time. The injection moulded products were then tested for shrinkage and product weight. The results showed that moulding temperature was the most influential parameter in getting a minimum shrinkage percentage, contributing 60.89%. Meanwhile, holding time contributes the most to achieving a maximum product weight (90.65%). After conducting a grey relation analysis and a confirmation test, the optimal parameters for shrinkage minimization and product weight maximization of motorcycle footstep cover are 210 of barrel temperature, 45 of moulding temperature, and 5 seconds of holding time. This research highlights the prospective applications of recycled polypropylene composite reinforced with ironwood powder for application as automotive parts
Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based on Well Log Data
Full text linkFacies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. Usually, the facies are classified manually by experienced geologists, so it takes a long time and is less efficient. In this paper, two machine learning (Support vector machine and K-Nearest Neighbor) were adopted to increase the effectiveness and shorten the time process of facies classification in Z Field, Indonesia. The machine learning algorithm was carried out in 4 steps, i.e. data selection, training phase, verification, and validation stage. The machine learning input data are density log, gamma ray log, resistivity log, SP log; and the output facies target are Sandstone, Siltstone, Claystone, and Limestone. The data is divided into train data for the training process and test data to validate the machine learning output. In Support vector machine results, the training accuracy is 70.1% and the testing accuracy is 47.4%, while in KNearest Neighbor results, the training accuracy is 70.1% and the testing accuracy is 63.3%. This result showed K-Nearest Neighbor has better accuracy than the support vector machine in facies classification in the Z field
Probability of Deuterium Atom Electrons in Momentum Space at Quantum Numbers n 3
Full text linkDeuterium is one of the isotopes of the hydrogen atom, which consists of 1 proton, 1 neutron, and 1 electron, also called a hydrogenic atom. The position of electrons in the atom cannot be determined with certainty because it is probabilistic. The probability of finding a deuterium atom electron in momentum space at quantum number n 3. This research aims to find the probability value of deuterium atomic electrons in momentum space at n 3. This research uses the mathematical theory study method through several stages, namely collecting the latest and relevant literature sources, making a simulation program, and then validating the simulation program with existing theory. If it has been validated, continue taking data that will be analyzed and then discussed in the results and discussion stage, and the last step is drawing conclusions. The results of this study show that the probability value for finding atomic electrons in momentum space will be more excellent with increasing integration limit values and the value of the principal quantum number (n)
Tuberculosis Detection using Gray Level Co-Occurrence Matrix (GLCM) and K-Nearest Neighbor (K-NN) Algorithms
Full text linkResearch 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%
Simulation of Multi Reservoir Operation Rules with Interconnected Tunnel and Water Transfer
Full text linkThe multi-reservoir operation rules require accuracy in developing its technical parameters. This is done to prevent operational failure in one of the reservoirs. The water transfer concept is to manage the water resources distribution between the receiving watershed and the donor watershed. The availability of transferable water must be prioritized, meeting the water demand of the donor reservoir. Storage capacity in both reservoirs aims to meet water demand, especially in the recipient. The elevation of the interconnecting tunnel is the minimum limit for water use in simulation. The interconnected tunnels' location and capacity will determine the multi-reservoir's operation rule. The interconnected tunnel in the Rukoh Tiro reservoir transfers water in the operation of the two reservoirs. The simulation is carried out in three seasons, considering the inflow of each watershed, the reservoir's downstream water demand, and the reservoir's technical conditions. The simulation results of the Rukoh Tiro reservoir operated simultaneously in all three seasons show that the fulfillment of irrigation water demand can reach 100% as needed. The water transfer process through interconnected tunnels occurs throughout the year. The reservoir operating rule is expected to be a reference in the multi-reservoir operation to obtain an optimal reservoir operating rule
Performance Assessment of Multi-story Building After 24 Years in Service
Full text linkAny public infrastructure has a set service life limit. In the Indonesian case, the public building has a 50-year design life. This paper presents a performance assessment of a multiple-story building in Aceh-Indonesia. A multi-story Faculty of Engineering Universitas Syiah Kuala building was used in this study. This multi-story building structure has been used for more than 24 years since it was built in 1998. This structure is 29.4 m long, 13 m wide, and 14.4 m tall in geometric terms. This study reveals how this three-story building behaves, including displacement, base shear, and structure performance level per ASCE 41-17 criteria. The processes in this study are broken down into various stages, including pushover analysis and comparing the building's current natural frequency. ETABS software was used to model building structures. According to the study, the building's performance is still more or less similar to the initial plan. Pushover in the X-direction (Push X) is believed to be immediate occupancy (IO), and pushover in the Y-direction (Push Y) is believed to be life safety (LS). The pushover analysis results for Push X suggested that the structure is safe and retains rigidity. Push Y indicated minor damage within the life safety category after a service life of 24 years. This pushover analysis indicated that the structure has reduced its rigidity, making it less able to resist further displacement. Based on the base shear, which experiences a displacement that is significantly greater than the estimate at the original planning stage, it is known that stiffness decreases
Green Synthesis and Characterization of Zinc Oxide Nanoparticles using Corchorus olitorius Leaf Extract
Full text linkGreen synthesis of metal oxide nanoparticles has gained prominence in recent years, resulting from the absence of toxic chemicals, low energy requirement, and eco-friendliness. This paper reports the green synthesis of zinc oxide nanoparticles (ZnO-NPs) using plant extract as a reducing agent. The ZnO-NPs were synthesized using Corchorus olitorius leaf extract and zinc acetate dihydrate, Zn (CH3COO)2.2H2O as precursor. The synthesized ZnO-NPs were characterized by the application of UVVis spectroscopy, Transmission Electron Microscopy (TEM), X-ray diffraction (XRD), Energy Dispersive X-ray Spectroscopy (EDX) and Fourier Transform Infrared Spectroscopy (FTIR). UV-vis indicated the reduction of zinc acetate dihydrate into ZnO-NPs by the leave extract. XRD and TEM revealed that the average size of the synthesized ZnO-NPs was 22 nm. The XRD pattern showed the hexagonal wurtzite crystalline nature of the synthesized ZnO-NPs. The elemental composition obtained from EDX showed that the synthesized ZnO-NPs are primarily composed of three elements: Zn (75.20 %), O (20.48.7%), and C (4.32). Examination of stretching and bonding in the ZnO-NPs using FT-IR revealed the presence of Zn-O bonding at 430.37403.93 cm-1
Thermo-Hydric Modeling of The Water Retention Curve Based on The Hydric Model of Van Genuchten
Full text linkIn this paper, we propose an extension for a model of unsaturated soils developed by Van Genuchten (1980) and obtain a thermos-hydric model to study the influence of temperature on the water retention curve. A brief presentation of the Model is described using the independent parameter modeling method. The proposed hydrometric Model makes it possible to predict, from the experimental measurements carried out on drainage-humidification paths for an ambient temperature, the WRC (water retention curve) at high temperatures while knowing the initial state of the soil studied (Compacted or in the form of a paste). We show in this Model the existence of the hysteresis phenomenon between the drainage and humidification path and the shift of the downward retention curves showing a slight decrease in the water content as the temperature increases. To validate this Model, three experimental results from the literature are simulated. The results obtained by simulating the experimental curves show the ability of the proposed Model to predict WRC at high temperatures. These results considerably reduce the number of experimental trials in geotechnical and geothermal unsaturated soils
Spatial Autoregressive Modeling on Linear Mixed Models for Dependency Between Regions
Full text linkThis study develops a linear mixed model (LMM) that includes spatial effects between regions with a spatial autoregressive model (SAR model). Between observations (regions) on that LMM are usually assumed to be independent. However, these assumptions are not always fulfilled due to dependency between regions. There are two important parts in spatial modeling: spatial dependence and spatial heterogeneity. In this study, we are concerned with the spatial lag or SAR models because dependency between variables of interest is easier to predict. On the other hand, all observations are real and can be directly seen from the data patterns. In addition, as a challenge for researchers to find all estimators while the values of the spatial dependence, sampling variance, and component variance are all unknown. This study aims to find all parameter estimators using a numerical approach and exact solutions. All exact estimators obtained are consistent estimators
Inorganic Solid Catalyst Derived from Fishbone Waste (Katsuwonus pelamis) for Transesterification of Coconut Oil into Biodiesel
Full text linkThis research has utilized fish bone wastes of tuna (Katsuwonus pelamis) collected at the Lampulo fish market in Banda Aceh. Inorganic oxides have been derived from those fish bone wastes through the decomposition method at high temperatures, namely the calcination process in air atmosphere at 900C for 4 hours. The physicochemical properties of obtained inorganic oxides were characterized using XRD and SEM-EDS techniques. The characterization results indicated that the composition of the calcined fish bone contained hydroxyapatite, CaCO3, and CaO, in which the hydroxyapatite phase has been the major component. Furthermore, the calcination process positively impacts improving the physical morphology and crystalline phase of inorganic oxides. Finally, those obtained inorganic catalysts based on fish bone waste have been applied for transesterifying Coconut oil with methanol, resulting in three main compounds: trimethyl borate, methyl laurate, and methyl octanoate