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Engineering Science Letter
Published by Indonesian Institute of Science and Technology Research
ISSN : 29618924     EISSN : 2961872X     DOI : https://doi.org/10.56741/esl.v1i02
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Engineering Science Letter is an international peer-reviewed letter that welcomes short original research submissions on any branch of engineering, computer science, and technology, as well as their applications in industry, education, health, business, and other fields. Artificial intelligence, image processing, data mining, data science, bioinformatics, computational statistics, electrical engineering, electronics engineering, telecommunications, hardware systems, industrial automation, industrial engineering, fluids and physics engineering, mechanical engineering, chemical engineering, and their applications are among the engineering and computer science topics covered by the journal. All papers submitted will go through a peer-review process to ensure their quality. Submissions must contain original research and contributions to their field. The manuscript must adhere to the author’s guidelines and have never been published before.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 67 Documents
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Comparative Analysis of Arduino-microcontroller based on PWM and MPPT Solar Charge Controller for Stand-alone Solar PV System in Charging Stations of Electric Vehicles Aung, Chan Myae; Mon, Ei; Htike, Than Than; Tun, Hla Myo
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001006

Abstract

This study especially focuses on Arduino-microcontroller based pulse width modulation (PWM) and maximum power point tracking (MPPT) solar charge controller design using buck topology for stand-alone solar photovoltaic (PV) application where the PV output voltage is larger than the load/battery voltage. It consists of the design calculation for solar charge controller, design simulation techniques, construction of the hardware circuit design and modified perturb and observe (P&O) MPPT algorithm by utilizing the variable duty cycle step size. In the PWM solar charge controller design approaches, the fixed duty cycle, D=89% is specified and in the MPPT approaches, the variable duty cycle step size is applied. The design approaches with simulation techniques are also performed by professional circuit IDE (Proteus). After completing the design approaches with simulation techniques, the construction of hardware circuit for both PWM and MPPT is also conducted in the research laboratory of Yangon Technological University (YTU). In this study, the real-time measurement (RTM) technique for practical measurements and their results are offered and compared with the results on simulation techniques. The practical operation, monitoring and recording of data are also executed by using Arduino microcontroller (ATmega328P) with Arduino Data Logger Shield. The comparison results on RTM practical approaches for both PWM and MPPT solar charge controllers are given and their performance specifications are also evaluated. Both of two approaches can safely be used to charge the 12V rechargeable battery in reality. However, RTM practical results confirm that the designed MPPT controller could be improved 9% efficiency than PWM technique. Therefore, the designed MPPT solar charge controller is more efficient than PWM technique and suitable for real world applications in 12V, 100Wp stand-alone PV system.
The Effect of Dividend Policy and Capital Structure on Firm Value: A Case Study in Vietnam Nguyen, Nghia
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001172

Abstract

Dividend policy represents the portion of corporate profit that companies pay to investors. Capital structure is a crucial corporate policy that indicates the ratio of debt to total assets. This paper aims to investigate the effect of dividend payout and capital structure on firm value in Vietnam. The study utilizes data from publicly traded companies on the Vietnamese Stock Exchanges. The analysis methods used include pooled OLS, and fixed and random effects models. The results reveal that dividend payout policy has a positive effect on the corporate value of Vietnamese publicly traded companies. The proportion of debt usage also exerts a positive effect on firm value. The findings show that corporate size and firm profitability have a significant and positive relationship with firm value. The study's results are useful for planning corporate dividend and capital structure policies.
Energy Efficiency Consumption of Building Planning Based on Indonesia Green Building Rules: A Case Study Salsabila Ramadhanti; Yatnanta Padma Devia; Alwafi Pujiraharjo
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001076

Abstract

This study evaluates the energy performance of the Tower B building in Riau Province, Indonesia, based on green building assessment criteria, with a focus on energy use efficiency. The initial design showed a total energy consumption of 2,255,923 kWh/year, corresponding to an Energy Use Intensity (EUI) of 95.46 kWh/m²/year, and earned a moderate energy score of 30 out of 46. Two operational strategies were proposed to address inefficiencies: (1) reducing the number of elevator units from six to four, and (2) implementing separate grouping of luminaires based on daylight exposure. Simulation results indicated that these strategies could reduce energy consumption in the elevator system by 33% and in the lighting system by 13%, without compromising user service standards. The combined application of both measures reduced total building energy use to 1,949,861 kWh/year (EUI 82.51 kWh/m²/year), yielding a 29% overall reduction and increasing the energy efficiency score to 38. While the results are promising, further research is needed to validate implementation through sensitivity analysis, behavioral modeling, and integration into regulatory frameworks. This study highlights the potential of adaptive operational strategies in optimizing building energy performance in tropical urban contexts.
Estimation of Blood Glucose Levels Using a Non- Invasive Infrared-Based Optical Sensor: A Pilot Study Mukhtar, Husneni; Zaelani, Muhammad Mugni; Nasrullah, Muhammad Rafy; Susanti, Hesty
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001218

Abstract

Blood glucose measurement is critical to diabetes management and prevents chronic complications such as neuropathy, nephropathy, and retinopathy. However, current methods are invasive, uncomfortable, and costly. Although several non-invasive approaches have been explored, no commercially available device offers a simple, affordable, and user-friendly solution for non-invasive blood glucose estimation, particularly one suitable for self-measurement outside clinical settings. This underscores the need for practical and inclusive alternatives. This study aimed to develop and evaluate a blood glucose estimation device using infrared LEDs to measure light transmittance through the fingertip. The research was conducted in two stages: initial testing using glucose solutions with varying concentrations (0.02, 0.06, 0.10, and 0.20 g/ml) and added red dye (0.05, 0.10, and 0.15 ml) to validate the sensor's response, followed by direct validation on human fingers against commercial blood glucose test strip readings. The results showed a strong positive correlation between sensor output and glucose levels, with a Pearson correlation coefficient of r = 0.995. Using a regression-based calibration model, the system achieved a mean absolute error (MAE) of 1.63 mg/dL, and a root mean square error (RMSE) of 1.72 mg/dL. Cross-validation, such as Bland-Altman analysis and Clarke Error Grid, was conducted to verify model robustness. These preliminary results suggest that the developed system holds strong potential as a simple, affordable, and non-invasive tool for blood glucose self-monitoring, especially in resource-limited settings. However, further validation on larger, more diverse populations is necessary.
BERT Model Implementation for Dynamic Sentiment Analysis of Pertamina on Social Media X Purba, Ronsen; Lubis, Rivaldi; Sikana, Nadya; Situmorang, Gilbert Fernando
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001139

Abstract

This study aims to investigate the dynamics of public sentiment on platform X in response to the Pertamina corruption scandal, exploring how trust and perception shifted before and after the incident. Utilizing BERT-based sentiment classification model trained on real-world social media posts, the model achieved a validation loss of 0.5078 and an F1-score of 82.12%, demonstrating strong predictive performance for large-scale sentiment analysis. Results revealed a significant rise in negative sentiment and a decline in positive sentiment following the public disclosure of the scandal on February 25, 2025, reflecting a deep erosion of public trust in Pertamina. Qualitative thematic analysis further identified a shift from neutral or positive discussions focused on service quality and innovation to emotionally charged critiques emphasizing betrayal, distrust and institutional failure. These findings highlight the value of integrating deep learning classification with qualitative insights to monitor real-time public opinion and institutional reputation. The study underscores the critical need for transparency and effective communication strategies during reputational crises to rebuild public confidence. Limitations include the focus on a single social media platform, suggesting future research should incorporate cross-platform and multilingual analyses. Practically, this research offers actionable insights for corporate crisis management and contributes to understanding social media’s role in shaping public trust and accountability in the digital age.
Optimization of Malaria Cell Image Classification Using Pretrained Resnet50 Architecture with Data Augmentation and Fine-Tuning Mulyani, Asri; Kurniadi, Dede; Rahmat, Agil
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001244

Abstract

Malaria remains a significant health concern, particularly in tropical regions such as Indonesia, where timely and accurate diagnosis is crucial for reducing transmission and mortality. Conventional diagnosis through microscopic examination is labor-intensive, time-consuming, and highly dependent on expert availability. This study proposes an automated malaria cell image classification model using a deep learning approach based on the pretrained ResNet50 architecture. The research framework adopts the SEMMA (Sample, Explore, Modify, Model, Assess) methodology to structure the development workflow. A total of 27,558 labeled blood cell images comprising two balanced classes, Parasitized and Uninfected, were used for training and evaluation. Two model configurations were tested: a baseline model without data augmentation or fine-tuning, and an optimized model that integrates both. Augmentation techniques such as rotation, flipping, shearing, zoom, and brightness adjustment were applied to increase data diversity, while fine-tuning involved unfreezing the last 20 layers of ResNet50 to adapt pretrained features to the malaria domain. Performance was evaluated using accuracy, precision, recall, F1-score, loss, and AUC-ROC. The optimized model achieved 97.63% accuracy, 0.996 AUC-ROC, and 0.2472 loss, outperforming the baseline accuracy of 92.84%. An ablation study analyzed the individual contributions of augmentation and fine-tuning, showing that both techniques play complementary roles, with fine-tuning having the greater impact. A McNemar test confirmed that the improvements were statistically significant (p < 0.05). These findings demonstrate that the optimized ResNet50 model is effective for malaria detection and holds promise for integration into real-time diagnostic systems in resource-constrained environments.
Analysis of Factors Affecting ERP Implementation Performance Using the Analytical Hierarchy Process (AHP): A Case Study at PT Multi Makmur Investama (Multives) Tangerang Silitonga, Roland Y.H.; Wandira Sembiring, Alem
Engineering Science Letter Vol. 4 No. 03 (2025): Article in Press - Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.001198

Abstract

The Indonesian packaging industry faces mounting pressure to align enterprise systems with evolving strategic and operational demands. This study investigates the performance of a mature Enterprise Resource Planning (ERP) system at PT Multi Makmur Investama (Multives), leveraging the Critical Success Factors (CSF) framework and Analytic Hierarchy Process (AHP) to identify and prioritize key determinants of ERP success. Ten CSFs were evaluated through expert pairwise comparisons and cross-validated via a perception survey of 51 ERP users. Results reveal ERP system quality (18.16%), top management support (14.19%), and user training (10.79%) as the most influential drivers. However, notable discrepancies emerged between expert prioritization and user satisfaction particularly in vendor support and training indicating underlying misalignments in long-term ERP usage. The study contributes a dual-layered evaluation model combining structured expert judgment and user-based validation, offering actionable insights for ERP optimization in emerging market contexts and extending theoretical discourse on ERP maturity evaluation.

Page 7 of 7 | Total Record : 67

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