Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Participatory blended learning model to enhance school and parent partnerships in elementary schools
Full text linkThis study aims to examine the effectiveness of a participatory blended learning model in enhancing knowledge and strengthening partnerships between schools and parents. A quasi-experimental pre-test–post-test group design was employed, involving 60 respondents selected as participants in the intervention. The model was designed to integrate online and face-to-face activities that promote collaborative learning and active parental engagement. The findings reveal that the participatory blended learning model significantly improved parental knowledge and partnership quality, as evidenced by statistically significant gains across five key dimensions: school-parent collaboration, digital-era parenting, positive parenting, healthy family routines, and parental involvement in school programs (p 0.05 for all dimensions). Additionally, improvements were observed in participation in parenting classes, inspiration class initiatives, family habit development, and involvement in school committees or associations. This study contributes to the field by demonstrating how participatory blended learning can serve as an effective strategy to bridge communication and cooperation gaps between schools and families, ultimately fostering a more inclusive and supportive educational environment
Active Disturbance Rejection Control for Unmanned Aerial Vehicle
Full text linkThis paper presents the design and analysis of a roll motion control system for a vertical take-off and landing of unmanned aerial car (VTOL-UAV) during the hovering flight phase. Ensuring stability and disturbance rejection during hovering is a significant challenge for UAVs, as external disturbances can lead to instability. To address these challenges, this study proposes an Active Disturbance Rejection Control (ADRC) strategy to enhance the system's roll stability and disturbance rejection. The primary contribution is the development of an improved ADRC system by integrating different types of extended state observers (ESO) with a Nonlinear-Proportional-Derivative (NPD) controller. The paper evaluates three ESO types—Linear (LESO), Nonlinear (NESO), and Fractional Order (FOESO)—for system state estimation and disturbance compensation. By combining the best ESO with NPD controller, an enhanced ADRC system is formed and its performance is compared against a conventional Proportional-Integral-Derivative (PID) controller. Numerical simulations performed using MATLAB demonstrate that ADRC significantly improves roll stability and disturbance rejection under both disturbed and undisturbed conditions. The results indicate that the LESO provides the best estimation accuracy, leading to superior system robustness. The ADRC system with LESO outperforms the PID controller in all test cases, particularly in disturbance rejection and stability. The study concludes that ADRC with LESO is an effective solution for improving VTOL-UAV roll motion control during hovering providing a promising approach for future UAV applications in dynamic environments
Intelligent Control of Rigid-Link Manipulators: A Systematic Review of Recent Advances and Future Trends
Full text linkAs robotic manipulators increasingly operate in dynamic and safety-critical environments, the need for intelligent control strategies that ensure adaptability, robustness, and real-time performance has become critical. While earlier reviews have addressed aspects of this domain, they often lacked systematic rigor, overlooked emerging hybrid and learning-based approaches, or provided limited quantitative synthesis. The research contribution is a PRISMA-compliant systematic review of 80 peer-reviewed studies on intelligent control of rigid-link manipulators (RLMs) published between 2016 and 2024, offering both qualitative and structured comparative analysis. The methods reviewed include PID, sliding mode control (SMC), fuzzy logic, artificial neural networks (ANN), reinforcement learning (RL), genetic algorithms (GA), and hybrid combinations. Studies were assessed according to methodological clarity, experimental validation, reported performance metrics, and publication impact. A comparative summary of 25 representative studies-selected based on citation impact, methodological rigor, and diversity of control approaches-highlights performance trade-offs and strengths across techniques. The findings indicate a growing shift toward hybrid intelligent controllers, which demonstrate enhanced adaptability in addressing nonlinear dynamics and uncertainties. However, most studies remain simulation-based, with limited real-world validation and reproducibility. Major research gaps include the lack of standardized benchmarking, insufficient explainability, and limited generalizability across application domains. These insights support the development of deployable, interpretable, and reliable robotic controllers, particularly for industrial automation and medical robotics, where transparency and safety are paramount
Real-Time Experimental Study of Speed Control for PMSM Drive System on OPAL-RT Simulator Using Radial Basis Function Neural Network
Full text linkThis paper addresses the problem of improving speed control accuracy and disturbance rejection capability for Permanent Magnet Synchronous Motors (PMSMs), which are widely used in industrial applications requiring high-performance drives. Conventional controllers such as PID often exhibit limited performance under nonlinear and time-varying conditions. The sliding mode control combined with a Radial Basis Function Neural Network (RBFNN) is proposed to enhance robustness and adaptability to overcome these limitations. The main contribution of this study is the integration of an adaptive RBFNN to estimate and compensate for unknown disturbances in real time, ensuring precise and stable motor operation. The theoretical stability of the system is guaranteed based on Lyapunov’s theory. The proposed method is implemented in a MATLAB/Simulink environment and tested on the OPAL-RT OP5707XG real-time hardware platform. The control system includes a speed loop using the RBFNN and a current loop for field-oriented control. The motor is subjected to varying speed commands in three stages to evaluate performance under dynamic conditions. Simulation results show that the RBFNN controller significantly improves speed tracking accuracy, reduces overshoot, and adapts better to sudden changes compared to conventional PID control. Real-time experimental results further confirm the effectiveness of the controller, despite the presence of noise and hardware delays. Current control performance also demonstrates better torque production and phase symmetry under dynamic loading with the RBFNN. A comparative analysis between simulation and experimental data highlights the practical applicability of the proposed approach
Cultural value transformation in Anang Ardiansyah's song lyrics: a hermeneutic inquiry into banjar people's identity
Full text linkThis research deeply examines how the lyrics of Anang Ardiansyah's songs reflect the dynamics of character values and cultural identity of the people of Banjarmasin, by using Paul Ricoeur's hermeneutic approach which consists of 5 stages: (1) Theme Identification; (2) Naive Understanding; (3) Deep Interpretation; (4) Fusion Horizon that allows researchers to capture the various layers of meaning contained in song lyrics. This systematic analytical process provides a solid methodological framework to examine the representation of fundamental values such as Islamic religiosity, local wisdom, patriotism, and social solidarity, which are inherent in the cultural identity of the Banjar people. This research analyses the symbolic and metaphorical meanings in four selected songs: Bastamiyah, Bismillah Kata Bamula, Puhun Rambai, and Paris Barantai. Through a systematic interpretive analysis, which involves a layer-by-layer interpretation to decipher the text based on its cultural and historical context, this study reveals that the lyrics represent fundamental values such as Islamic religiosity, local wisdom, patriotism, and social solidarity that are deeply rooted in the cultural identity of the Banjar people. The findings show that the songs function as a medium for transmitting and preserving cultural values, bridging tradition and modernity. The significance of this research lies in identifying the mechanisms through which traditional art has a role in transmitting and preserving cultural values
Machine learning-based residential load demand forecasting: Evaluating ELM, XGBoost, RF, and SVM for enhanced energy system and sustainability
Full text linkAccurate forecasting of electrical power load is essential for properly planning, operating, and integrating energy systems to accommodate renewables and achieve environmental sustainability. Therefore, this study introduces different machine learning (ML) methods, including support vector machines (SVM), random forests (RF), extreme learning machines (ELM), and extreme gradient boosting (XGBoost) to predict hourly electricity demand using electricity consumption and temperature data for train and test ML models. The data is processed by autocorrelation function (ACF) and cross-correlation function (CCF) to determine the appropriate lag time for the inputs. Furthermore, ML model accuracy is assessed using coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE). Results show that the ELM model achieved the highest R² in both summer (0.971) and winter (0.868), outperforming the other models in accuracy R² and error reduction (MAE and RMSE). ELM also more effectively captured load fluctuations. The result of this research has applications for load demand forecasting in the proper planning and operation of the residential grid. The results help estimate load demand and provide useful guidance for residential grid planning and management by determining the best techniques for precisely estimating load demand and identifying domestic energy consumption pattern
Narrative structure, symbolic meaning, and cultural expression in contemporary Indonesian horror cinema
No full textThis study investigates narrative strategies in contemporary Indonesian horror films to understand how they convey cultural meanings and engage audiences. While horror is often dismissed as entertainment, Indonesian horror serves as a cultural mirror, reflecting societal fears, spiritual beliefs, and identity struggles. The study focuses on eight films released between 2019 and 2024, selected for their narrative complexity, cultural relevance, and critical reception. Using qualitative narrative analysis, the research applies Seymour Chatman's distinction between story and discourse alongside classical and modern narrative theories by Bordwell, Todorov, Genette, and others. The analysis identifies three-act and five-act structures and nonlinear, circular, and episodic narratives. These structures enhance suspense, emotional engagement, and thematic depth. The findings show that Indonesian horror films blend local folklore, Islamic rituals, and communal values with experimental storytelling. For example, Siksa Kubur uses fragmented timelines to depict trauma, while Qodrat integrates religious exorcism into its plot structure. Such strategies deepen audience immersion and articulate culturally specific anxieties. This research contributes to Indonesian cinema studies by highlighting how narrative form shapes meaning and emotional impact. It offers a framework for analyzing horror beyond Western paradigms and provides insights into how traditional and modern storytelling coexist in Southeast Asian media. Academically, it advances narrative theory in a non-Western context. Practically, it supports filmmakers and cultural producers in using horror to engage with social issues and connect with global audiences through culturally grounded storytelling
Android-based STEM-AR and its contribution to elementary school students' environmental literacy
Full text linkThis study is motivated by the low environmental literacy and academic achievement of elementary school students. The study aims to measure the effect of Android-based STEM-AR on students' environmental literacy. A quantitative research method with a One Group Pretest-Posttest Design was used. A total of 31 fifth-grade elementary school students in Yogyakarta, Indonesia, were randomly selected from nine public schools. The research instruments included a lesson plan and an Augmented Reality (AR) medium accessible via Android smartphones. STEM was used as a reference for structuring subject matter. The treatment was conducted four times, each lasting 70 minutes. Students' environmental literacy was measured before and after the treatment using a validated multiple-choice test. Data analysis employed a t-test with a 5% significance level. The Paired Sample Test results showed a sig(2-tailed) value of 0.001 0.05, which led to the rejection of the null hypothesis and acceptance of the alternative hypothesis. This study contributes to proving that Android-based STEM-AR positively influences elementary school students' environmental literacy
The impact of after-school activities to enhance students’ academic performance in Vocational High School in Indonesia
No full textAfter-school activities (ASA), also known as extracurricular activities, can be found in various forms at all academic levels. These activities could include English Club, sports, debate, or drama. They have become an essential component of school life for students. In order to comprehend this effect, the author intends to describe how extracurricular activities were used as touchpoints to enhance students' academic performance. The focus of the study was 500 students of Vocational High School in Bekasi, Indonesia. Specifically, this study utilized a mixed research approach. There were two instruments used in this study; a student survey and student reflections. The findings demonstrated that after-school activities affect the students’ academic performance especially in speaking skills. They also showed their improvement in self-esteem, critical thinking, and discipline
Powertrain Conversion of a Small Agricultural Tractor from Diesel Engine to Permanent Magnet Synchronous Motor
Full text linkThis paper presents the powertrain conversion of a small diesel-powered tractor into an electric tractor or electric off-road vehicle (EORV), offering a cost-effective alternative to purchasing a new electric model, which may be financially challenging for small-scale farmers. Given that electricity is generally cheaper than diesel fuel in Malaysia, the conversion approach aims to reduce long-term operational costs while maintaining or improving performance. The primary contribution of this work is a systematic and practical method for electric tractor conversion. The process begins with analysing the existing performance and operational requirements of the diesel tractor, followed by the selection of suitable components—namely, the electric motor, battery cells, and other associated systems. These components are then integrated into the tractor, and initial testing was performed. A speed run test was conducted to evaluate the power capability of the converted tractor. Results indicate that the electric motor delivers higher power and speed compared to the original diesel engine. The onboard energy monitoring device recorded a noticeable current spike and voltage sag during acceleration, as expected. The motor power was calculated from the recorded voltage and current data. The data show that the motor output exceeds the rated power of the original engine, suggesting that the system can handle higher loads. Some challenges encountered during the conversion process include the high initial cost, limited availability of components that meet performance requirements, and technical challenges in ensuring the durability and efficiency of the modified drivetrain. In conclusion, further testing under various load conditions is necessary to fully evaluate energy consumption and system performance in real agricultural environments