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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 116 Documents
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YOLOv8-Based Tomato Ripeness Detection with Color and Texture Features Luh Putu Ary Sri Tjahyanti; Made Santo Gitakarma
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002559

Abstract

The advancement of precision agriculture requires intelligent and automated solutions to enhance crop monitoring and post-harvest management. Accurate recognition of tomato ripeness is a critical stage in the agricultural supply chain, as misclassification can lead to quality degradation and significant economic losses. This study proposes a deep learning-based approach for tomato ripeness detection by integrating handcrafted color features and Gray Level Co-occurrence Matrix (GLCM)-based texture features with YOLOv8. The dataset comprises tomato images categorized into three final ripeness classes—green, semi-ripe, and fully ripe—obtained by grouping multiple physiological maturity stages into unified model classes to reduce visual ambiguity and collected under diverse lighting and background conditions. Candidate tomato regions are first localized by YOLOv8; HSV and CIELAB color descriptors and GLCM texture descriptors are then extracted from each region and fused with the corresponding deep representation for ripeness classification and confidence refinement. Experimental results based on five-fold cross-validation show that the proposed method achieves a mean Average Precision (mAP@0.5) of 96.7%, compared with 92.5% for standard YOLOv8. The results show improved discrimination between visually similar ripeness stages, particularly under non-uniform illumination. The study demonstrates the potential of domain-informed feature fusion for smart farming, automated sorting, and quality control systems.
Microstructural Characterization of AISI 1045 Steel after Quenching with Various Cooling Media Syaiful Arif; Bambang Ali Gunawan; Miftah Ghiffari; Joni Arif; Alfian Ady Saputra; Wahid Hasim
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002584

Abstract

AISI 1045 steel is a medium-carbon steel widely used for machine components due to its favorable combination of strength, toughness, and machinability. Its mechanical properties can be enhanced through heat treatment, specifically quenching using various cooling media. This study aims to analyze the effect of different cooling media on the microstructural changes of AISI 1045 steel following the quenching process. An experimental method was employed using three cooling media variations: 25% NaCl solution, SAE 10W-30 oil, and distilled water. Specimens were heated to an austenitizing temperature of 850°C with a 60-minute holding time, followed by quenching for 5 minutes in each respective medium. Microstructural characterization involved metallographic preparation comprising grinding, polishing, and etching with 5% nital solution followed by observation under a metallographic microscope at 200× and 400× magnifications. Observations revealed that the raw material was dominated by ferrite and pearlite structures. After quenching, a martensitic structure formed, with the quantity and distribution varying according to the cooling medium used. The 25% NaCl solution produced the most dominant and relatively uniform martensitic structure, followed by distilled water, whereas SAE 10W-30 oil resulted in a lower proportion of martensite, with ferrite and pearlite remaining dominant. These differences indicate that the cooling rate characteristics of the quenching media influence phase transformation and the resulting microstructure of AISI 1045 steel. Based on the observations, the 25% NaCl solution provided the most intensive cooling effect compared to distilled water and SAE 10W-30 oil.
Gradient Boosting Ensemble and SHAP-Based Explainability for Financial Literacy Classification in Urban Indonesia Zulpa Salsabila; Tri Wulandari Ginting; Juliana Damayanti Manurung
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002585

Abstract

Although national surveys report rising financial literacy in Indonesia, losses from investment fraud and illegal peer-to-peer lending continue to increase, suggesting that aggregate indices obscure differences across knowledge, behavior, and attitude. This study developed a four-class literacy classification framework using gradient boosting models and SHAP-based explanations, drawing on an online survey of 606 respondents in urban North Sumatra. The instrument, adapted from OJK/SNLIK, consisted of nine knowledge, fourteen behavior, and four attitude items. SMOTE-NC was applied only within cross-validation training folds, so the validation and test data contained no synthetic observations. CatBoost obtained the highest cross-validated Macro F1 (0.8950) and achieved a test accuracy of 87.91% and a Macro F1 of 0.8587, comparable to XGBoost and Logistic Regression. Because the classes were derived from the same items used as features, these models largely approximate the scoring rule. A model based only on demographic and contextual variables, which avoids this dependence, reached a Macro F1 of 0.5347 against a majority-class baseline of 0.1579. Attitude items showed the highest per-feature SHAP contribution (0.321), partly owing to their larger scoring weight, although this dimension was less reliable (α = 0.6167). Gold price awareness, decision confidence, and risk preference were the most discriminative items.
Performance Optimization of Conventional Lathes in the Shipbuilding Industry Integrating OEE and TPM Ridwan Usman; Anggi Oktaviani; Rini Setiowati; Agus Iskandar; Ayu Nurul Haryudiniarti
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002595

Abstract

PT DPKB manufactures ship components such as M19 nuts and M20 bolts using conventional lathes. In its operations, the company faces challenges such as high downtime, rapid wear of cutting tools, coolant clogs, chip buildup, and unstable machine performance, all of which prolong production time and hinder the achievement of targets. This study aims to measure the effectiveness of conventional lathes, identify the dominant factors contributing to performance decline, and formulate strategies for improvement. The method used is a quantitative descriptive approach that integrates Total Productive Maintenance (TPM), Overall Equipment Effectiveness (OEE), the Six Big Losses, the Fishbone Diagram, and the 5W+1H analysis. The results show that the OEE for M19 nuts was 53.89% (Availability 76.40%, Performance Efficiency 77.97%, Quality 91.55%) and for M20 bolts was 19.30% (Availability 81.65%, Performance Efficiency 28.58%, Quality 82.58%), far below the Japan Institute of Plant Maintenance benchmark (85%). Operational efficiency is a key critical factor driven by speed-reduction losses and equipment failures resulting from a lack of preventive maintenance, clogged cooling channels, limited operator skills, and an unsupportive work environment. The novelty and contribution of this study lie in the formulation of a TPM framework tailored to heterogeneous shipyards, providing tactical guidance based on the 5W+1H action plan and the TPM pillars to optimize self-maintenance, periodic cleaning, and work standardization to improve the operational efficiency of shipyards.
Exploring Climate-Responsive Wisdom of Traditional Lampung Architecture for Contemporary Sustainable Design Achmad Zoelkarnaen Rasjid
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002629

Abstract

Traditional Indonesian architecture holds climate-responsive strategies that are relevant to sustainable design, but these principles have not been systematically translated into contemporary architecture. This study aims to identify and analyze the principles of climate responsiveness in traditional Lampung houses and their potential for today's sustainable design. The study uses qualitative case studies with field observations, architectural documentation, simple thermal condition measurements, and semi-structured interviews with 15 informants consisting of residents, traditional leaders, and architectural practitioners. The data were analyzed thematically and comparatively. The results identified an interconnected climate-responsive configuration in traditional Lampung houses, characterized by site- and wind-responsive orientation, elevated floors approximately 1.2–2.0 m above ground, opposing openings that facilitate cross ventilation, large roof volumes, shading elements, local timber materials, and adaptive spatial organization. Spot measurements showed lower indoor temperatures than simultaneous outdoor temperatures during the observed periods; however, these measurements are interpreted as indicators of passive thermal response rather than direct evidence of thermal comfort. The study contributes a Lampung-specific climate-responsive design framework that translates vernacular principles into measurable criteria for contemporary sustainable architecture.
Determinants of Natural Stone Procurement Effectiveness: An Empirical Analysis of Supplier Performance in Construction Projects in Bali A. A. A. Made Cahaya Wardani; A. A. Diah Parami Dewi; I Gusti Agung Ayu Istri Lestari
Engineering Science Letter Vol. 5 No. 03 (2026): Engineering Science Letter - Articles in Press
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002632

Abstract

 Selecting natural stone suppliers for construction projects is a complex issue that cannot be determined solely by price, given the variations in quality, timeliness, capacity, proximity, flexibility, and supplier reliability. There is an urgent need for an objective supplier selection model to support procurement effectiveness regarding cost, quality, scheduling, and supply continuity. This study aims to analyse the factors determining supplier performance and their structural influence on procurement effectiveness. An explanatory quantitative approach was employed, involving a sample of 150 respondents selected via purposive sampling. Data were collected using a closed-ended questionnaire with a 1–5 Likert scale, distributed both in person and via Google Forms (shared through WhatsApp). Data analysis was conducted using the PLS-SEM method (via SmartPLS software), encompassing descriptive analysis, evaluation of the outer and inner models, and bootstrapping. The results indicate that 98.67% of the data were valid; outer loadings ranged from 0.781 to 0.879, AVE values ​​from 0.756 to 0.839, and Cronbach’s Alpha values ​​from 0.852 to 0.903. The model yielded an R² value of 0.742 and a Q² value of 0.587. Reliability exerted the strongest influence (β = 0.286; p < 0.001), followed by quality (β = 0.247; p < 0.001), whereas supplier proximity did not show a significant influence (β = 0.087; p = 0.082). The findings reveal a multidimensional and performance-based approach to supplier evaluation. In conclusion, reliability is a strategic determinant of procurement effectiveness. The implication is that the supplier selection process should prioritize consistency, quality, timeliness, and continuity of supply. This model strengthens evidence-based decision-making and reduces reliance solely on price and proximity in procurement practices.

Page 12 of 12 | Total Record : 116

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