International Journal of Advances in Applied Sciences
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Rock slope kinematics analysis by Markland method of the Bener District, Purworejo Regency, Central Java, Indonesia
Get PDFBener District, Purworejo Regency, Central Java, Indonesia, located in the Kulon Progo Mountains can be classified as a high-risk area. Many experts and researchers have studied landslides, but there has been little research on rock slope kinematics. In fact, when such a rock slope is unstable and poorly monitored, it has the potential to endanger the community or facilities at the adjacent site. This is why slope kinematics research is required. To complete this study, rock kinematics analysis using the Markland method was performed on six representative slopes. The assessment results show that Kaliwader slope A, Kaliwader slope B, and Argosari slope each tend to collapse with wedge failure, Kaliwader slope D and Wadas slope have the potential for wedge failure and planar slide, but Kaliwader slope C does not. Despite their steep inclination, slopes that are likely to fail are strongly related to the presence of geologic structures, particularly joints, and faults, at the sites. The findings of this study will be helpful in the development of landslide vulnerability zones in the context of disaster mitigation
Low-carbon no-idle permutation flow shop schedulling problem: giant trevally optimizer vs African vultures optimization algorithm
Get PDFGreenhouse gas emissions continue to increase due to increased energy consumption. One of the largest emission-contributing sectors is the manufacturing industry. Therefore, the manufacturing industry is required to minimize carbon emissions. One of the efforts to solve the emission problem is to minimize machine downtime throughout the production procedure, which stands for no-idle permutation flowshop scheduling (NIPFSP). This article uses two metaheuristic algorithms, giant trevally optimizer (GTO) and African vultures optimization algorithm (AVOA), to solve the carbon emission problem. Both algorithms are tested on 3 cases with 30 runs for every population and iteration. To compare the outcomes of each algorithm, an independent sample t-test was employed. The results show that the GTO algorithm has better results than the AVOA algorithm on small and large case data. The findings indicate that both the GTO and AVOA algorithms yield comparable results when applied to medium-sized research datasets, suggesting their effectiveness in such scenarios
Groundwater recharge estimation using chloride mass balance method on the southern slope of Merapi Volcano, Indonesia
Get PDFGroundwater is a main resource for the majority of Indonesian people as a source of clean water to meet their daily needs. The increase in groundwater use is unavoidable due to increasing development in Indonesia, especially in Yogyakarta. Groundwater recharge is important in the hydrological cycle to meet groundwater needs. Therefore, this study aims to estimate groundwater recharge by the chloride mass balance (CMB) method on the southern slope of Merapi Volcano in Yogyakarta, Indonesia. This research was conducted in the rainy and dry seasons from August 2022 until January 2023. This research collects annual rainfall near the study area from the Meteorology, Climatology, and Geophysics Agency (BMKG) Yogyakarta station, monthly data collected from eighteen samples of groundwater station, and monthly data collected from fifteen samples of rainwater in the study area. The chemical content of groundwater and rainwater samples is analyzed using argentometry to obtain chloride concentration. The result of annual rainfall in the study area is 3,603.878 mm/year. The average chloride concentration in rainwater is 1.1 mg/L, while the average chloride concentration in groundwater is 8.015 mg/L. The CMB method calculation showed that the recharge in the study area ranges from 171.65 to 1,711.29 mm/year. The groundwater recharge has a positive correlation with elevation and rainfall. High groundwater recharge is also found in the northern area due to fractured lava aquifer
Generating intelligent agent behaviors in multi-agent game AI using deep reinforcement learning algorithm
Get PDFThe utilization of games in training the reinforcement learning (RL) agent is to describe the complex and high-dimensional real-world data. By utilizing games, RL researchers will be able to evade high experimental costs in training an agent to do intelligence tasks. The objective of this research is to generate intelligent agent behaviors in multi-agent game artificial intelligence (AI) using deep reinforcement learning (DRL) algorithm. A basic RL algorithm called deep Q network is chosen to be implemented. The agent is trained by the environment's raw pixel images and the action list information. The experiments conducted by using this algorithm show the agent’s decision-making ability in choosing a favorable action. In the default setting for the algorithm, the training is set into 1 epoch and 0.0025 learning rate. The number of training iterations is set to one as the training function will be repeatedly called for every 4-timestep. However, the author also experimented with two different scenarios in training the agent and compared the results. The experimental findings demonstrate that our agents learn correctly and successfully while actively participating in the game in real time. Additionally, our agent can quickly adjust against a different enemy on a varied map because of the observed knowledge from prior training
MCDM-AHP and PROMETHEE methods integrated for base service strategy vendor evaluation and selection
Get PDFBusiness competition is very important in controlling product-savvy customers. Strong basic service techniques will be the main factor that binds vendors as the final destination in the supply chain through the strength of business network processes. This research aims to create a strategic basis for evaluating and selecting vendors through the integration process services of the multi-criteria decision-making method analytic hierarchy process (MCDM-AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) methods. Empirical studies show how this approach can provide optimal decision support for the vendor evaluation and selection process. Eight different types of criteria are required in its apps and must be realized as a barometer of the strategic basis for selecting vendors so that business processes are of high quality. These criteria include quality of goods, payment methods, payment terms, minimum transactions, discounts, delivery times, inventory, and service. The optimal weight for each criterion will be determined based on its importance to the synthesis process and its feasibility tested using mathematical algebra matrices and expert choice apps. Decision-making was based on the results of ranking evaluation of selected vendors through the development of 342 preference matrices, ten vendors were deemed worthy of acceptance and nine other vendors were rejected
The effect of adding sodium tripolyphosphate on thiobarbituric acid value, crispiness, and organoleptic on salted egg crackers
Get PDFCrackers are one of the dry foods that can experience volume expansion when fried. Salted egg crackers are a form of innovation and product diversification in crackers, which are made using ingredients containing starch and various other additives. This study aims to determine the exact concentration in the use of sodium tripolyphosphate as a crunch in dough on the crispness, thiobarbituric acid (TBA) value, and organoleptic of the salted egg crackers. There were 4 sodium tripolyphosphate (STPP) concentration treatments, namely 0% (T1), 0.25% (T2), 0.5% (T3), and 0.75% (T4). This research method consists of experimental design, research procedures, parameter tests, and data analysis. The results of the analysis of the TBA value showed that the difference in the concentration of STPP affected the rancidity of the salted egg crackers, where the higher the concentration of STPP, the higher the TBA value. Crispness and organoleptic analysis showed the highest value and overall preference, namely 0.75% (T3) treatment. This study concludes that the difference in the concentration of the addition of sodium tripolyphosphate affects the crispness of crackers
Physical and chemical characteristics of Chitofudregs nugget in comparison to commercial nugget
Get PDFThe study aims to compare the physical characteristics (water holding capacity and cooking loss) and chemical characteristics (moisture, protein, fat, ash, carbohydrate content, and total calories) of Chitofudregs nugget with commercial nuggets. Four categories of nuggets which are Fiesta, So Good, Nugget Curah, and Chitofudregs nugget (FT, SG, NC, and Chitofudregs) were determined as treatments in this study with 5 repetitions for each category. The experimental method of this research was a randomized design complete (RDC). Physically, Chitofudregs had the highest water-holding capacity and the lowest cooking loss among all commercial nuggets (p<0.05) so there were not many nutrient losses during the processing. Chemically, Chitofudregs contained higher water content than one of the commercial-NC nuggets while the protein and ash content was lower than the two types of commercial nuggets (FT and SG) with carbohydrate content which was also lower than the NC commercial nuggets (p<0.05). The fat content and total calories of chitofudreg were the lowest among all commercial nuggets (p<0.05). Chitofudregs are combination nuggets whose physical quality is as good as commercial nuggets with specific chemical characteristics and has potency as a diet product because it is low in fat and calories
Silica extract from Malang beach sand via leaching and sol-gel methods
Get PDFMany silica minerals are found in beach sands. One of its beach sands is in Bajul Mati beach sand which contains high silica. The silica can be extracted using existing methods, but it is less environmentally friendly. In this research, the extracting process of silica from the sand of Bajul Mati beach (South of Java-Indonesia) has been carried out through a method that is low-cost and more environmentally friendly. The purpose of this study was to characterize extracted silica with instrumentation results and economic analysis. The method of extracting silica from beach sand was via leaching and sol-gel methods: i) leaching with 7M HCl,ii) the formation of clear sodium silicate solution (Na2O.SiO2),iii) sol-gel: sodium silicate solution titrated with oxalic acid (H2C2O4) 1 M until pH 6 was obtained and silicite Si(OH)4 was formed, and iv) characterization with X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier transform infrared (FTIR), and scanning electron microscopy (SEM) with economic analysis. The result showed that extracted silica has a cristobalite structure based on XRD analysis. The purity of silica (% Wt Si) reached 93.9% based on XRF analysis. FTIR analysis has identified silanol, siloxic, and siloxane groups. The SEM analysis shows that silica (SiO2) particles tend to form agglomerations about ∼1 μm. In addition, economic analysis results showed that this method will support implementation in the future, so silica has been produced by this developed method
Nutritional evaluation of spent and uninoculated mushroom substrate of Pleurotus ostreatus grown on cassava peels and sawdust
Get PDFThis study aims to evaluate the role of edible fungi in the biodegradation of mushroom substrate by comparing the mineral and proximate composition of a pasteurized substrate before inoculation (BI) with the spent mushroom substrate (SMS) of Pleurotus ostreatus cultivated on cassava peels and sawdust. The experiment was conducted at the Federal University of Technology, Owerri, Imo State Nigeria. The treatment for this investigation comprised different levels of wheat bran namely: T1 (C/N 17:0 in the control), T2 (C/N ratio 17:1), and T3 (C/N ratio 17:3). 2% lime was added to the substrate to stabilize the pH. The experiment was laid out in a completely randomized design (CRD) which was replicated three times. The mineral and proximate compositions were determined using standard procedures. The data generated were subjected to analysis of variance (ANOVA) at (p = 0.05). The result obtained from this investigation reviewed that the mineral composition before substrate inoculation was significantly higher than those obtained from the SMS which were in the range: of Na (0.10-0.17 mg/kg), Mg (0.25-0.40 mg/kg), Ash (1.56-2.65%), Ca (0.62-1.40 mg/kg), K (0.25-0.42 mg/kg), and P (0.11-0.44 mg/kg) while the proximate composition is in the range: dry matter (81.6-93.3%), N (0.18-0.31%), crude protein (CP) (1.13-1.94%), crude fiber (2.84-4.82%). This result revealed that significant quantities of the nutrients unlocked by Pleurotus ostreatus were assimilated into the mushroom fruit bodies. Therefore, Pleurotus ostreatus could be used to enrich cassava peels and sawdust substrates which can further be utilized in the formulation of livestock feeds. However, further studies are recommended especially in evaluating more nutritional indices of the substrate
Internet of things with NodeMCU ESP8266 for MPX-5700AP sensor-based LPG pressure monitoring
Get PDFThe use of liquefied petroleum gas (LPG) cylinders as fuel has become a basic need for the community. LPG is more efficient than oil stoves, but LPG also poses a danger. The dangers contained in gas cylinders cause users to be afraid to check the availability of gas in cylinders because the checking process must be directly close to the gas cylinder. Because of this danger, users do not check gas availability, causing it to run out of gas when cooking. To solve this problem, a system is needed to detect the availability of LPG contents, which can be monitored remotely so that users will feel safe because they are not close to gas cylinders. The condition of gas cylinder availability can be remotely monitored using the internet of things (IoT) method. Therefore, an IoT-based LPG pressure monitoring tool was designed. A tool designed using the MPX-5700AP sensor is useful for detecting gas pressure values in LPG cylinders. IoT is used to monitor LPG pressure using the Blynk application. The buzzer module is a tool for sending sound signals as information on the condition of gas cylinders. The NodeMCU ESP8266 microcontroller processes and sends data to the Blynk application. System testing is carried out in three conditions: full, close to empty, and empty. The results of this test showed an error value of 3.41% and an accuracy rate of 96.59%