Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Capability of Hybrid Long Short-Term Memory in Stock Price Prediction: A Comprehensive Literature Review
Full text linkStocks are financial instruments representing ownership in a company. They provide holders with rights to a portion of the company's assets and earnings. The stock market serves as a means for companies to raise capital. By selling shares to the public, companies can obtain funds needed for expansion, research and development, as well as various other investments. Though significant, predicting stock prices poses a challenge for investors due to their unpredictable nature. Stock price prediction is also an intriguing topic in finance and economics due to its potential for significant financial gains. However, manually predicting stock prices is complex and requires in-depth analysis of various factors influencing stock price movements. Moreover, human limitations in processing and interpreting information quickly can lead to prediction errors, while psychological factors such as bias and emotion can also affect investment decisions, reducing prediction objectivity and accuracy. Therefore, machine processing methods become an alternative to expedite and reduce errors in processing large amounts of data. This study attempts to review one of the commonly used prediction algorithms in time series forecasting, namely hybrid LSTM. This approach combines the LSTM model with other methods such as optimization algorithms, statistical techniques, or feature processing to enhance the accuracy of stock price prediction. The results of this literature review indicate that the hybrid LSTM method in stock price prediction shows promise in improving prediction accuracy. The use of optimization algorithms such as GA, AGA, and APSO has successfully produced models with low RMSE values, indicating minimal prediction errors. However, some methods such as LSTM-EMD and LSTM-RNN-LSTM still require further development to improve their performance
A Combination of INC and Fuzzy Logic-Based Variable Step Size for Enhancing MPPT of PV Systems
Full text linkThe significance of using the variable step Incremental Conductance (INC) technique in Maximum Power Point monitoring (MPPT) of photovoltaic (PV) systems resides in its capacity to improve the efficiency of energy conversion. This is accomplished through the constant measurement and comparison of incremental changes in current and voltage, precisely monitoring the maximum power point amidst changing environmental conditions. This traditional INC-MPPT approach has two primary disadvantages. Initially, it employs a predetermined scaling factor that necessitates human adjustment. Furthermore, it adjusts the inclination of the PV characteristics curve to modify the step size. This implies that even little changes in PV module voltage will have a substantial impact on the total step size. As a result, it shifts the operating point away from the intended reference maximum power point. The objective of this work is to improve the efficiency of traditional INC by overcoming the constraints associated with step size modifications. This is achieved by using a fuzzy logic (FL) technique to adjust the step size adaptively in response to environmental changes. The presented INC-FL-MPPT successfully achieves MPPT for a PV system under enhanced steady-state and transient-state settings. The results demonstrate the superiority of the suggested approach compared to three distinct MPPT strategies, namely Perturb and Observe (PO), Classical INC, and PO-FL technique
A Novel Sea Horse Optimizer Based Load Frequency Controller for Two-Area Power System with PV and Thermal Units
Full text linkThis study introduces the Sea Horse Optimizer (SHO), a novel optimization algorithm designed for Load Frequency Control (LFC) in two-area power systems including photovoltaic and thermal units. Inspired by the interactive behaviors of seahorses, this population-based metaheuristic algorithm leverages strategies like Brownian motion and Levy flights to efficiently search for optimal solutions, demonstrating quicker and more stable identification of global and local optima than traditional algorithms. The proposed SHO algorithm was tested in a two-region power system containing a photovoltaic system and a reheat thermal unit under three different scenarios. In the first scenario, the frequency response of the algorithm to a 0.1 p.u. load change in both regions was examined. In the second scenario, the algorithm's frequency response to sudden load changes from 0.1 p.u. to 0.4 p.u. was tested. Finally, the algorithm's frequency response was examined against different levels of solar irradiance for sensitivity analysis. This study compared the performance of the SHO-optimized controller with the optimization algorithms reported in the literature, including the Genetic Algorithm (GA), Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), and Modified Whale Optimization Algorithm (MWOA). In this context, the optimization of PI controller gain parameters based on the ITAE metric resulted in SHO algorithm achieving the best performance with values of 2.5308, followed by WOA at 4.1211, FA at 7.4259, and GA at 12.1244. In tests, SHO significantly outperformed these algorithms in key performance metrics, such as Settling Time, Overshoot (M+), and Undershoot (M-). Specifically, SHO achieved 98.94% better overshoot and 85.25% reduced undershoot than GA, and concluded settling times 52.79% faster than GA in the first scenario. Similar superior outcomes were noted in subsequent tests. These results underline SHO's efficacy in enhancing system stability and control performance, marking it as a significant advancement over conventional LFC methods
Prognostic Real Time Analysis of Induction Motor
Full text linkVariable speed induction motors controlled by variable frequency drives are used for a variety of industrial applications. Monitoring and prognostic occurrence of faults in induction motors is vital for reducing the downtime and accidents. The proposed work focuses on failures in induction motors owing to bearing misalignment and insulation failure in the stator that results in abnormal vibration and temperature rise in the motor. This research intends to improve the dependability and safety of industrial operations by identifying faults in their early stages using advanced methods such as vibration analysis and thermal monitoring. This work focuses on fault prognosis in induction motor through vibration data, which is analyzed using Daubechies orthogonal db10 wavelet transformation. The neural network algorithm optimizes the analyzed results to enable real time fault detection. The temperature of the stator is measured to estimate the expected lifetime of the insulator. The real time vibration and temperature data is measured and transferred to prognostic model build in MATLAB using ATMEGA 32 controller and the results are validated for good, allowable and not permissible conditions of motor based on ISO 10816 vibration levels for Class I motors. The improved accuracy and efficiency of real-time fault detection have the potential to reshape maintenance strategies and enhance the overall reliability of variable speed induction motors
Design and Implementation of Smell Agent Optimizer for Parameters Estimation of Single and Double Diode in PV System: A Comparative Analysis
Full text linkOne of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits. The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement
An Overview of the Role of the Regional Inflation Control Team (TPID) on Inflation in Banjar Municipality from an Islamic Economic Perspective
Full text linkInflation is the process of increasing prices continuously and is defined as a continuous decrease in currency value. The characteristics of Indonesia’s inflation are much influenced by the shock factor. The shock factor could be caused by production disruption due to natural disasters such as floods and long dry seasons which greatly affect the inflation of raw food materials.The composition of Indonesia’s inflation is influenced by 80% regional inflation and 20% central inflation, so it is deemed necessary for the regional government to participate in controlling the national inflation along with the central government and Bank Indonesia. Following suit of the prior establishment, TPIN was formed which consisted of the TPIP and TPID. The role of TPID in controlling inflation is an ideal concept to control inflation through the creation of an ideal market.The perspective of Islamic economics analyses how inflation occurs, whether due to natural conditions, human error, or a combination of these two factors. The prices of goods and services are important to control inflation and the prices need to provide a sense of justice for both producers and consumers
Exploring the efficacy of the singing method for teaching nglegena javanese letters to fourth-grade students in an elementary school
No full textStudents' difficulties in learning Javanese script are caused by several factors, such as challenges in distinguishing one character from another, low interest and motivation to learn, and limited access to educational materials and resources. This study aims to evaluate the effectiveness of the singing method as a learning strategy in teaching Javanese Nglegena script. This study uses a participatory qualitative approach with data collection techniques through interviews and observations of research subjects, namely fourth-grade students at an elementary school in Yogyakarta. The research sample consisted of 28 students, consisting of 16 boys and 12 girls. The results of the study showed that the singing method provided a more positive and interesting learning experience. Quantitatively, there was an increase in students' interest and motivation in learning, which contributed to a more interactive and enjoyable learning process. The main contribution of this study is the development of a more effective Javanese Nglegena script learning model through the singing method. This model can be adopted by Javanese language educators to increase students' interest in learning Javanese script. In addition, this method has also been proven to help students memorize material faster and maintain memory longer
Enhancing the Performance of Power System under Abnormal Conditions Using Three Different FACTS Devices
Full text linkIn this paper, a comparison between Flexible Alternating Current Transmission System (FACTS) devices including Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) for providing a better adaptation to changing operating conditions and improving the usage of current systems. The power system using FACTS devices is presented under different conditions such as single phase fault and three phase fault. A digital simulation using Matlab/Simulink software package is carried out to demonstrate the better performance including the voltage and the current of the presented system using FACTS that located between buses B1 and B2 under different faults types. The results obtained investigate that the presented system gives better response with FACTS as compared to not using them under abnormal conditions besides, the UPFC gives better performance of power system under several faults as compared to STATCOM or SSSC as It can absorb reactive power in a manner which significantly reduced the fault current. It is demonstrated that UPFC can reduce the peak fault current at bus B1 ‎to 63.85% of its value without ‎using FACTS devices under line to ground fault and 79.18% under three line to ‎ground fault whereas STATCOM and SSSC reduce it ‎to (75.21, 94.35%) and (75.40, 94.68%), respectively
The role of hyperlocal media in cultural preservation: an analysis of the Three Cs implementation at Galuh Prambanan TV in Klaten
Full text linkThis paper explores implementing the "Three Cs" principles (Community, Commitment, and Continuity) proposed by Agnes Gulyas and Kristy Hess within the context of hyperlocal media as a cultural preservation. A case study was conducted on Galuh Prambanan TV in Klaten, a local media outlet focused on Javanese cultural content. The research employs a qualitative approach by gathering data through in-depth interviews, direct observation, and case study analysis. The primary informants in this research are media practitioners and local cultural figures. The findings indicate that local community engagement is crucial in ensuring cultural preservation. The community's long-term commitment to the production and consumption of local cultural content is also a critical factor in the success of this preservation. Continuity in the presentation and management of content through applying the hyperlocal media model, as demonstrated by Galuh Prambanan TV, enables operational sustainability and strengthens relationships with the community. Implementing these principles positions Galuh Prambanan TV as an active agent in preserving Javanese culture while providing an example of how hyperlocal media can support cultural preservation in the face of globalization and modernization challenges. Therefore, this study concludes that applying the "Three Cs" is crucial for the sustainability of hyperlocal media and the successful preservation of local culture. Consequently, this research provides practical contributions to developing more effective cultural preservation strategies through hyperlocal media
Visual Analysis and the application of Islamic law in farm animal vocabulary learning videos for children
Full text linkThis study analyzes the visual expression and application of Islamic legal principles, particularly iqtina ash-shurah, in the animated video "Learning Vocabulary: Names of Farm Animals" produced by Yufid Kids. This video serves as an educational medium for early childhood learners to acquire vocabulary related to farm animals. The study is important as it addresses the intersection of Islamic legal principles and visual media, providing a framework for creating educational content that aligns with sharia while remaining engaging and effective. The content of the wimba used is a visual representation of livestock depicted in a simple and unrealistic way, adhering to sharia principles and avoiding realistic depictions of living beings. Visual expressions in the video consist of four types: first, expressing space, which clearly displays the location and environment of animals; second, expressing motion, which includes animations that illustrate animal activities, making it easier for children to grasp vocabulary; third, external expressions that indicate time and space through scene transitions, facilitating contextual shifts in the narrative; and finally, stating importance, which emphasizes key information through visual elements such as color and size to draw attention to essential learning components. From the perspective of Islamic law, the analysis focuses on the application of iqtina ash-shurah, which permits the use of simplified and non-detailed images of living beings, and the inclusion of thayyibah sentences to reinforce Islamic values. The research uses a qualitative descriptive method through visual and sharia analysis. The findings demonstrate that the video successfully integrates effective visual expressions with adherence to Islamic principles, providing an interactive, educational, and Islamic learning experience. This research contributes to the field of Islamic education and visual media by offering a model for developing sharia-compliant educational content, highlighting the theoretical and practical value of visual expressions in reinforcing Islamic values in early childhood learning