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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 8 Documents
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Search results for , issue "Vol. 4 No. 03 (2025): Engineering Science Letter" : 8 Documents clear
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): 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.
Development and Evaluation of a Laminated Bamboo Frame for Electric Scooters: A Preliminary Prototype Herawan, Safarudin Gazali; Martalogawa, Ismail Azizi; Saputra, Azqy Nur Farenzy; Moenartioso, Ahmad Hanif; Ghazali, Ihwan
Engineering Science Letter Vol. 4 No. 03 (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.001314

Abstract

This study presents the design, fabrication, and evaluation of a hybrid electric scooter frame constructed from laminated Gombong bamboo and aluminium. The objective was to address environmental concerns in personal mobility by reducing reliance on high-carbon materials and improving battery safety. A CAD-based design was executed in Autodesk Inventor using bamboo beams for primary structure and aluminium joints for mechanical stability. Laminated bamboo was processed through drying, chemical treatment, and gluing. Mechanical properties were evaluated via tensile and compressive tests, achieving a tensile strength of 289 MPa. A 72V lithium-ion battery pack composed of 18650 cells was assembled with BMS integration. The resulting prototype exhibited a total frame weight of 4.8 kg and a 30 km range per charge. The integration of laminated bamboo with aluminum joints provides preliminary evidence of feasibility and highlights bamboo’s potential as a renewable material for lightweight mobility applications. These results provide an initial prototype-level demonstration of laminated bamboo as a viable material for sustainable transport applications.
Forecasting Electricity Demand In Indonesia: Recommendation for Prediction Models to Support PLN’s RUPTL Aini, Zulfatri; Rahmadeni; Alaqsa, Tengku Reza Suka
Engineering Science Letter Vol. 4 No. 03 (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.001696

Abstract

The Electricity Supply Business Plan (RUPTL) prepared annually by PLN still shows a high error rate in predicting electricity consumption, exceeding 10% in various provinces, such as North Sumatra (36.92%), DKI Jakarta (24.87%), West Kalimantan (40.24%), and South Sulawesi (31.56%), due to the limitations of the linear regression method used in the RUPTL. This study aims to evaluate and recommend the best electricity consumption forecasting model based on artificial intelligence using a Feed Forward Backpropagation Neural Network (FFBP-NN) combined with six training algorithms: Bayesian Regularization (BR), Conjugate Gradient (CG), Levenberg-Marquardt (L-M), Gradient Descent (GD), Quasi-Newton (Q-N), and Resilient Backpropagation (RB), resulting in a total of 13 algorithmic combinations. The data used consists of RUPTL indicators for DKI Jakarta from 2018 to 2023. Testing results of the 13 training functions on the FFBP-NN demonstrate that the TRAINOSS (Quasi-Newton) algorithm achieves the best performance with the lowest Mean Square Error (MSE) of 0.0000065546 and Mean Absolute Percentage Error (MAPE) of 0.06696%. This algorithm outperforms the linear regression method currently used in PLN’s RUPTL, which has a MAPE of approximately 21.14%. The second and third best algorithms are TRAINSCG and TRAINLM, with MAPE values of 0.09455% and 0.10020%, and MSE values of 0.0012160450 and 0.0012229340, respectively. The FFBP-NN model trained with TRAINOSS is highly recommended as the primary alternative to support long-term electricity load planning such as in PLN’s RUPTL.
Hybrid Machine Learning for Crime Prediction in Indonesia toward Society 5.0 Sikana, Nadya; Lubis, Rivaldi; Situmorang, Gilbert Fernando; Prisella, Naomi
Engineering Science Letter Vol. 4 No. 03 (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.001359

Abstract

Crime remains a major social challenge in Indonesia, requiring innovative approaches to enhance prevention and law enforcement. This study proposes a hybrid machine learning framework that integrates the Temporal Fusion Transformer (TFT) for time-series forecasting and Extreme Gradient Boosting (XGBoost) for classification and feature analysis. Using socio-economic and demographic data from the Indonesian Central Bureau of Statistics (2010-2023) across 38 provinces, the framework aims to predict crime incidence and classify crime resolution effectiveness. The results show that TFT effectively captures temporal dependencies, achieving robust forecasting accuracy (R2 = 0.9893), while XGBoost delivers high classification performance (Accuracy = 98.87%). Feature importance analysis highlights the dominant role of case resolution rate, government consumption expenditure, school participation rates and life expectancy in shaping crime patterns. Compared to baseline models such as LSTM and Random Forest, the hybrid TFT + XGBoost approach demonstrates superior balance between accuracy, robustness and interpretability. These findings provide actionable insights for policymakers to design data-driven crime prevention strategies, align with Indonesia’s digital transformation agenda, and support the vision of Society 5.0.
Forecasting Rice Price Volatility Utilizing BiLSTM-SHAP to Ensure National Food Stability Manurung, Juliana Damayanti; Sikana, Nadya; Simamora, Fandi Presly; Manurung, Zoni Zikro
Engineering Science Letter Vol. 4 No. 03 (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.001360

Abstract

Rice price volatility in Indonesia remains a persistent economic issue, partly driven by climate variability and fluctuations in national rice production, prompting the government to resort to substantial annual imports. However, the extent to which domestic production factors and weather conditions influence future rice prices has not been quantitatively evaluated. This study aims to forecast short-term rice prices in Indonesia by integrating multiple time-series features, including rice prices, harvested area, paddy production, and weather features, using a Bidirectional Long Short-Term Memory (BiLSTM) network. Daily data from 2013 to 2024 were collected from the National Statistics Agency, Food Price Panel, and the Meteorology and Climatology Agency. Chronological split was applied for training, validation, and testing to preserve temporal dependency. The optimal model predicts rice prices seven days ahead using 256 hidden units, achieving MAE of 128.84 IDR, RMSE of 157.98 IDR, and R² of 0.694. SHAP analysis shows that historical rice prices have the strongest contribution with a SHAP value of 0.969652, significantly higher compared to other features. The results demonstrate that integrating agricultural and climatic inputs improves predictive performance while providing interpretable insights into price-forming factors.
Simulation of Updraft and Downdraft Gasification Using Computational Fluid Dynamics (CFD) for Production of Hydrogen-Rich Syngas from Cow Manure Waste Utami, Amaliyah Rohsari Indah; Salma, Anindya Nabila; Muchtar, Daffa Rayhan Betha; Sintawardani, Neni; Suwandi
Engineering Science Letter Vol. 4 No. 03 (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.001397

Abstract

Biomass gasification offers a promising route to low‑carbon hydrogen, yet the operating conditions and reactor configuration governing hydrogen-rich syngas remain insufficiently compared across practical regimes. This study aims to quantify the effects of gasifier type (updraft vs. downdraft), operating temperature, and superficial velocity on hydrogen production performance, with emphasis on the syngas H2/CO ratio. Computational fluid dynamics simulations were implemented to model devolatilization, oxidation, and reduction pathways under steady-state assumptions, while systematically varying temperature (680-800°C) and air superficial velocity (0.0025-4 m/s). Model validation against experimental reference data demonstrated good agreement, with relative errors ranging from 5.95% to 6.93%. The results indicate that a downdraft configuration operated at 680°C and 2 m/s maximizes the H2/CO ratio, achieving a value of 2.091, outperforming alternative settings in terms of hydrogen yield and energy efficiency, albeit with higher variability than the updraft configuration. Increasing air flow beyond this optimum diminishes the H2/CO ratio due to enhanced oxidation, whereas raising the temperature to 800°C generally reduces the average H2/CO across both configurations. These findings establish a practical operating window for hydrogen‑rich syngas from livestock waste and highlight the need for rigorous process control to manage variability in downdraft operation. The study provides evidence-based guidance for gasifier design and operation, aiming to achieve efficient and renewable hydrogen production.
Analysis of the Effect of Damdex Addition to Concrete Mixture on Compressive Strength Sari, Endah Murtiana; Probokusumo; Rokhmah, Alfiya; Ashidqi, Muhamad Dzaky; Rahmat; Junaedi, Thomas
Engineering Science Letter Vol. 4 No. 03 (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.001420

Abstract

This study aims to determine the compressive strength and modulus of elasticity of concrete with the addition of Damdex variables to obtain the best composition. This research method is classified as quantitative research conducted at PT. Fresh Beton Indonesia Batching Plan BSD. In this study, research was conducted using two different concrete mixtures, namely 1 Pc: 2 S: 3 Gr and 1 Pc: 3 S: 2 Gr, each of which was supplemented with Damdex at concentrations of 0.0%, 0.2%, 0.4%, and 0.6%. According to the study's results, the highest compressive strength and modulus of elasticity were achieved in a concrete mixture of 1 Pc: 2 S: 3 Gr, with a variable addition of Damdex at 0.2%, resulting in a compressive strength of Fc 15.11 MPa and a modulus of elasticity of 18975.061 MPa. Meanwhile, the lowest compressive strength and modulus of elasticity results were obtained in the concrete mixture of 1 Pc: 2 S: 3 Gr with the variable addition of Damdex 0.6%, with a compressive strength of Fc 12.90 MPa and a modulus of elasticity of 17049.89 MPa. In the concrete mixture of 1 Pc: 3 S: 2 Gr, the compressive strength and modulus of elasticity were smaller compared to the concrete mixture of 1 Pc: 2 S: 3 Gr, with the highest results in the variable addition of Damdex 0.2%, with a compressive strength of Fc 9.89 MPa and a modulus of elasticity of 13846.477 MPa. Compressive strength and elastic modulus were measured at 28 days in accordance with SNI 1974:1990/2847 procedures. Among the tested mixtures, the 0.20% Damdex addition achieved the highest average compressive strength and elastic modulus. Within the tested conditions, 0.20% Damdex provided the best average performance; however, further work with larger samples and additional durability metrics is needed to confirm this trend.
A Fuzzy Logic Approach for Temperature Stability in Infant Incubator Systems Syaifudin; Kholiq, Abd.; Maghfiroh, Anita Miftahul
Engineering Science Letter Vol. 4 No. 03 (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.001451

Abstract

An infant incubator is a critical life-support device that provides thermal regulation for premature or low-birth-weight infants who are unable to maintain stable body temperature. Precise temperature control is essential, as instability and prolonged transient responses can increase health risks. Conventional on-off control methods commonly used in basic incubator systems often result in slower stabilization and higher temperature error. Therefore, this study aims to design and implement a baby incubator temperature control system using a fuzzy logic controller (FLC) integrated with a DS18B20 temperature sensor to improve thermal stability. The proposed system was implemented on a physical incubator prototype and evaluated experimentally. System performance was assessed based on dynamic response characteristics, including rise time, peak overshoot, and settling time. Experiments were conducted using three temperature setpoints: 32°C, 35°C, and 36°C. To ensure measurement accuracy, system performance was validated using an Incu Analyzer as a reference device. The experimental results show that the fuzzy logic-based control system achieved a steady-state temperature error of approximately 1% across all setpoints. The maximum observed settling time after peak overshoot was 100 seconds, indicating faster and more stable temperature regulation compared with conventional on-off control methods reported in previous studies. These results demonstrate that fuzzy logic control is effective in handling nonlinear thermal dynamics and improving temperature stability in infant incubator systems. This study focuses on technical performance evaluation; therefore, further investigations related to safety assessment and regulatory compliance are required before clinical implementation. Nevertheless, the proposed system shows strong potential as an intelligent temperature control approach for the development of neonatal incubator technology.

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