Journal Title : Jurnal Ilmiah Teknik (JUIT) Initials : JUIT Frequency : Januari, Mei, September Print ISSN : 2828-6936 Online ISSN : 2828-6901 Editor in Chief : Dr. Abdul Muchlis, ST., MT DOI : 10.56127 Publisher : Asosiasi Dosen Muda Indonesia Sponsored : (Kami Memasang Tarif Untuk Iklan Disini Harap Hubungi ADMIN) Jurnal Ilmiah Teknik (JUIT), ISSN: 2828-6936 (cetak), ISSN: 2828-6901 (online) adalah jurnal yang ditujukan untuk publikasi artikel ilmiah yang diterbitkan oleh Asosiasi Dosen Muda Indonesia dan di payungi Oleh Yayasan Dosen Muda Indonesia. saat ini sudah terakreditasi SINTA 5 Sampai 2027 sesuai dengan keputusan Direktur Jendral Pendidikan Tinggi, Riset dan Teknologi Nomer 10/C/C3/DT.05.00/2025. Jurnal ini adalah jurnal Ilmu Teknik yang bersifat peer-review dan terbuka. Bidang kajian dalam jurnal ini termasuk sub rumpunIlmu Teknik Mesin, Elektro, Kimia, Sipil, Metalurgi, Teknik Industri, Teknik Informatika, Sistem Informasi dan Ilmu Komputer. Jurnal Ilmu Teknik menerima artikel dalam bahasa Inggris dan bahasa Indonesia dan diterbitkan 3 kali setahun: Januari, Mei, September. Silakan buat Artikel Template baru lalu kirimkan naskah Anda. Indexed by:
Comparative Analysis of Concrete Curing Using the Water Curing Method and the Geotextile Non-Woven Membrane Curing Method and Their Effects on Concrete Compressive Strength
This study compares the effectiveness of conventional water curing and non-woven geotextile membrane curing on concrete compressive strength, an important issue because curing quality strongly influences early hydration and strength development while field constraints often limit continuous water-based curing. A quantitative experimental design was conducted in a controlled laboratory setting using 150 mm concrete cube specimens produced with a standardized mix design; specimens were assigned to either full water immersion or pre-moistened non-woven geotextile membrane curing. Compressive strength data were collected at 7, 14, and 28 days and analyzed descriptively by comparing average strengths and strength development trends between both curing methods. The results show that strength increased with age under both regimes, while membrane curing consistently achieved slightly higher average compressive strength than water curing, with the largest difference at 7 days (28.56 MPa vs. 26.95 MPa) and smaller gaps at 14 days (33.04 MPa vs. 32.58 MPa) and 28 days (38.61 MPa vs. 37.99 MPa). These findings suggest that non-woven geotextile membrane curing can be a practical alternative to water curing, particularly where continuous immersion or water supply is difficult to maintain, because it may provide better early-age moisture retention without compromising later-age strength. The originality of this study lies in presenting direct experimental evidence comparing immersion-based curing and an accessible non-woven geotextile membrane approach across multiple curing ages under consistent specimen production conditions.
Optimization of Booster Pump Performance Through Reliability Centered Maintenance (RCM) and Failure Mode and Effect Analysis (FMEA) at Wisma PMI
Maintenance of the booster pump machine at the PMI guesthouse building located on Jl. Wijaya No. 63 South Jakarta is an obligation for operational management. The booster pump machine is the core of driving the distribution of water needs throughout the building, data obtained from engineering in 2023 experienced damage 70 times, the damage had an impact on tenant complaints because the engine was loud and frequent. To overcome water supply problems and also the noise so as not to cause complaints for consumers which had a long- term impact on reducing rental space occupancy in the property business, engineering and evaluation of the maintenant system was immediately carried out using the reliability centered maintenant (RCM) method and failure mode and effect analysis. (FIMEA) is one of the steps taken in an effort to resolve complaints regarding the operational failure of the booster pump. After analyzing the data using the RCM strategy and also FIMEA to determine the potential and damage level scores, if the results of the analysis are applied it is estimated that an optimization of the booster pump system can be obtained with the damage level decreasing by up to 20% and also reducing the engine noise level by up to 20 db.
Closed Loop: Integrated Water, Nutrient, and Energy Recovery Systems for Sustainable Dairy Production (Case: Dairy Farming)
The dairy industry is very important to the economy, but it has big problems with sustainability since it doesn't use resources well and doesn't handle waste well. Eco-Efficiency (13.1%) and Technical Efficiency (58.7%) are still very low in Serbia because of ongoing structural inefficiencies. In Indonesia, where 90% of dairy farms are operated by smallholders, an estimated 84% of manure is discharged untreated, contributing to greenhouse gas emissions and eutrophication. To solve these problems, we need to use Circular Economy ideas, such as closed-loop nutrient, energy, and water flows and integrated resource recovery. This review evaluates opportunities, sustainability gains, and barriers to implementing closed-loop systems across the dairy supply chain. The objectives include assessing farm-level efficiency, quantifying environmental and economic benefits of manure-derived resource recovery, evaluating circular feed substitution, and analysing biogas adoption barriers among smallholders. The research integrates findings from Stochastic Frontier Analysis, Life Cycle Assessment and Costing, Multi-regional Input–Output analysis, membrane-based water reuse models, and system dynamics, complemented by qualitative surveys of Indonesian farmers. Integrated recovery systems yielded carbon-negative results (up to –1790 kg CO₂ eq/year) and significant economic advantages ($825–$1,056/year). Biogas cut down on the consumption of LPG by about 45%. Circular feeds made more milk and had less of an effect, while treating whey membranes slashed the need for fresh water by 67–90%. Closed-loop solutions make dairy farming much more sustainable, but they need help from policymakers to be able to grow because of high investment costs and ongoing structural inefficiencies.
OHS Work Procedure Implementation and CSMS Performance in Construction Projects
High accident risk in construction projects indicates that OHS documentation alone is insufficient without consistent on-site implementation of safe work procedures. Objective: This study evaluates the implementation of Occupational Health and Safety (OHS) based work procedures and analyzes their impact on the performance of the Construction Safety Management System (CSMS) in the Architectural Christian Center construction project, addressing the gap between administrative and operational compliance. Methodology: An evaluative design with combined descriptive quantitative and qualitative approaches was applied. Data were collected through questionnaires administered to project personnel, field observations, and reviews of OHS-related documents. Analysis compared on-site practices with applicable regulations and the CSMS theoretical framework, supported by interpretation of questionnaire and observation results to identify implementation gaps. Findings: Normatively, OHS-based work procedures meet CSMS documentation requirements; however, operational implementation remains ineffective. Work procedures and Job Safety Analysis (JSA) are still treated primarily as administrative instruments and are not consistently integrated into daily work execution methods. Worker compliance is uneven: PPE use shows relatively better adherence than compliance with work procedures and JSA, indicating that risk control is still oriented toward individual protection rather than optimized through administrative controls and engineering-based work methods. Additionally, positioning OHS personnel within the contractor’s internal organization may reduce the independence and effectiveness of safety supervision due to pressures related to time, cost, and progress targets. Implications: Improving CSMS performance requires stronger integration of work procedures and JSA into routine execution, more consistent enforcement of procedural compliance, and strengthened supervisory authority to reduce reliance on PPE. Originality: This study explicitly links OHS work procedure implementation to CSMS performance while highlighting the contractor-internal OHS organizational structure as a structural factor affecting enforcement effectiveness, and provides actionable recommendations to embed safety within engineering-based construction execution methods.
Domestic Architectural Transformation and Cultural Continuity: The Case of Fala Kanci in Ternate City
Rapid urbanization in Ternate City has intensified pressure on domestic housing and accelerated changes in traditional dwellings such as Fala Kanci, raising challenges for adaptation without losing cultural identity. Objective: This study investigates how urbanization pressures, socio-economic conditions, and cultural values interact in shaping the spatial, material, and functional transformation of Fala Kanci domestic architecture across different urban contexts in Ternate City. Method: A qualitative approach was applied through field observations, in-depth interviews, questionnaires, and visual documentation of 36 Fala Kanci houses located in interior, peripheral, and urban core zones. Data were examined using thematic and comparative analysis to identify transformation patterns and cross-zone variations. Findings: Transformations occur unevenly. Urban core areas show the most intensive spatial expansion, increased material substitution from organic to industrial components, and broader functional diversification. Peripheral areas display mixed adaptation patterns, while interior areas exhibit stronger intergenerational continuity and greater preservation of traditional forms. Despite extensive physical modification, key cultural values communal interaction, family orientation, and symbolic identity remain embedded in spatial organization and selected architectural elements. Implications: The findings support context-sensitive strategies for architects, planners, and heritage practitioners to balance housing adaptation with cultural continuity in rapidly urbanizing island cities. Originality: This research contributes an integrative household-level account linking urbanization dynamics, socio-economic strategies, and cultural persistence an aspect often underexplored in vernacular architecture and urban studies.
Quality Control Analysis Using the Seven Quality Control Tools in the Production Process of Crinkle Culotte Pants at CV Damar Konveksi
The garment manufacturing industry in Indonesia faces challenges in maintaining product quality, particularly in the production of crinkle culotte pants at CV Damar Konveksi. Product defects, especially in the sewing and finishing stages, have resulted in lower quality and production efficiency. Objective: This study aims to analyze and improve quality control in the production process of crinkle culotte pants at CV Damar Konveksi, identifying dominant defects and their causes to recommend corrective actions. Methodology: A quantitative approach was used, collecting primary data from direct observations and secondary data from internal records. Data were analyzed using check sheets, scatter diagrams, control charts, Pareto diagrams, and fishbone diagrams to identify defect types, frequencies, and root causes. Findings: Out of 450 units produced, 21 were defective (4.6% of total production). The Pareto diagram revealed that asymmetrical stitching and excessive sewing threads accounted for 71.4% of the defects. Control chart analysis showed the process remained within control limits, though significant quality fluctuations occurred across periods. The fishbone diagram identified human factors, suboptimal work methods, and poor machine conditions as the main causes of defects. Implications: The study recommends implementing operator training, regular machine maintenance, better enforcement of standard operating procedures, and enhancing the quality inspection system to reduce defects and improve production efficiency. Originality: This research provides valuable insights into quality control within garment manufacturing, offering a practical framework for improving product quality and operational efficiency. The use of the Seven Quality Control Tools in CV Damar Konveksi adds originality by providing actionable recommendations for similar manufacturing environments.
Rupiah Banknote Classification Using MobileNetV2 Based on Image Data
Visually impaired individuals often struggle to independently identify Indonesian rupiah denominations because banknotes share similar colors, patterns, and layouts, increasing the risk of errors during cash transactions. Purpose: This study aims to develop an offline, image-based banknote denomination recognition system on Android that can provide accessible assistance without relying on internet connectivity. Methodology: A quantitative experimental design was applied using a dataset of 4,340 banknote images covering 14 classes (seven denominations with front and back sides). The classifier was built with MobileNetV2 using transfer learning, supported by data augmentation and hyperparameter optimization, and evaluated using validation accuracy and F1-score. The trained model was converted to TensorFlow Lite and integrated into a Flutter-based Android application with text-to-speech output for user assistance. Findings: The proposed model achieved 96.20% validation accuracy with an average F1-score of 0.95, indicating strong performance for lightweight on-device inference. Implications: The system can be deployed in real time on smartphones to support inclusive and safer cash handling for visually impaired users, and it demonstrates the feasibility of offline deep learning for accessible financial technology. Originality: This study provides an end-to-end offline solution for Indonesian rupiah recognition that combines a lightweight deep learning model, on-device deployment, and text-to-speech feedback while distinguishing both sides of multiple denominations, offering practical value beyond approaches that depend on cloud inference or limited class coverage.
Web-Based Sales System Development for Adi Jaya Electrical Store with Midtrans Payment Gateway Integration
MSMEs/UMKM remain a major driver of local economic activity, yet many still depend on offline, cash-based transactions that constrain operational efficiency. Digital sales platforms are therefore increasingly necessary to support faster, more reliable, and cashless purchasing processes. Objective: This study aims to develop and deploy a web-based sales system for Adi Jaya Electrical Store an MSME located at Ruko Taman Aster, Telaga Asih, Bekasi to improve transaction efficiency through online ordering and cashless payment. Methodology: The study adopts an applied information systems development approach using the Waterfall model. The system was implemented using PHP and a MySQL database, with requirements derived from field observation and interviews with the store owner. Functional verification was conducted using scenario-based black-box testing to assess whether key features operated according to the specified design. Findings: The website supports online product browsing and purchasing for electrical supplies (e.g., sockets, LED lamps, and cables) and integrates Midtrans as a payment gateway to facilitate non-cash transactions. Black-box testing indicates that the implemented functions and features operated as expected and were consistent with the design specifications. The system has been deployed and is accessible at https://adijaya.wuaze.com/. Implications: The platform provides a practical model for MSMEs to digitize sales operations, potentially improving transaction speed, reducing manual processing, and strengthening sales administration through structured order and payment management. Originality: This research delivers an operational MSME e-commerce implementation that combines end-to-end sales functionality with payment gateway integration and documented functional verification, extending prior work that often reports prototype development without demonstrable deployment readiness.
Usability Analysis of the Authentication Feature in the Andal by Taspen Application Using the System Usability Scale Method
This study evaluates the usability of the authentication feature in the Andal by Taspen application for pensioners, focusing on challenges faced by elderly users, as initial reviews indicate issues with its effectiveness. Objective: This study aims to assess the usability of the Andal by Taspen authentication feature using the System Usability Scale (SUS) method, identify usability issues affecting elderly users, and provide recommendations for improvement. Specifically, the study focuses on evaluating whether the selfie-based authentication process meets the needs of elderly pensioners, who may face challenges in digital literacy and physical limitations. Methodology: This quantitative study involved distributing the System Usability Scale (SUS) questionnaire to PT Taspen pensioners in the Cempaka Putih District, Jakarta. The responses were analyzed using the SUS method to generate a usability score for the authentication feature and to identify areas for improvement. Findings: The findings reveal that the Andal by Taspen authentication feature received a SUS score of 61, which corresponds to Grade D on the SUS scale, with an adjective rating of "OK" and an acceptability range classified as "Marginal (Acceptable)." The primary issues identified include difficulties in the self-authentication process, particularly for elderly users, as well as challenges related to digital literacy and physical constraints. Implications: The study recommends the development of an heir-based authentication feature to assist elderly pensioners in the authentication process. Additionally, the study emphasizes the importance of improving digital literacy among elderly users to ensure that they can effectively use digital platforms. Originality: This research offers a unique contribution to the field of digital public services by providing an empirical evaluation of selfie-based biometric authentication in mobile applications for elderly users, a topic that remains underexplored in existing literature. The findings provide valuable insights into the usability challenges faced by older adults, particularly in the context of pension services, and propose actionable solutions to enhance accessibility and usability.
Optimization of Transmission Systems in Rice Threshers and Straw Choppers: Enhancing Energy Efficiency and Productivity through V-Belt and Pulley Design
Rice threshers and straw choppers are essential to improve post-harvest efficiency, yet small-scale machines often experience capacity loss and wasted motor power due to non-optimal V-belt–pulley transmission design (e.g., incorrect pulley ratio, belt length, and speed matching), which reduces speed stability and increases mechanical losses. Objective: This study aims to analyze and optimize the V-belt–pulley transmission system of a combined rice thresher–straw chopper to improve power utilization and achieve target operating speeds for both processes. Methodology: A quantitative engineering approach was applied using analytical transmission design calculations and design verification through mechanical layout/simulation. Key parameters were derived from machine requirements and transmission relations, including processing capacity, force and torque, shaft speed, power demand, pulley diameters, transmission ratios, belt speed, belt length, center distance, and wrap angle. Findings: Using a 1 HP (750 W), 1450 rpm electric motor, the designed system achieved a calculated threshing capacity of 90 kg/h and straw chopping capacity of 84 kg/h under a 2-minute batch assumption. The required output power was 270.60 W (threshing) and 245.97 W (chopping), while the motor-side power demand was 308.27 W and 280.30 W, respectively, resulting in a total requirement of 588.57 W (≈78% motor power utilization). With an 80 mm driver pulley, the selected driven pulleys were 105.45 mm for the thresher (1100 rpm; ratio 1.32) and 116 mm for the chopper (1000 rpm; ratio 1.45). The belt speed was 6.06 m/s, with belt lengths of 2110 mm (A83) and 1480 mm (A58). Implications: The results provide practical parameter benchmarks for designing low-cost small-scale agricultural machines that better match motor power to required speeds and torque, reducing transmission mismatch. Originality: This study presents a parameter-complete V-belt–pulley design framework for a dual-function thresher–chopper, explicitly linking capacity targets to transmission sizing and motor power utilization.
Chaos-Based Digital Image Encryption Using Arnold’s Cat Map Permutation and Duffing Map Diffusion: A Python Desktop Implementation
Digital images are widely used for identification, communication, and information exchange, yet their large size, high pixel correlation, and uneven intensity distribution make them vulnerable to theft, manipulation, and statistical inference, thereby requiring encryption mechanisms tailored to image characteristics. Purpose: This study proposes a chaos-based permutation–diffusion scheme that combines Arnold’s Cat Map for pixel permutation and the Duffing Map as a keystream generator for diffusion to strengthen digital image encryption and improve resistance to unauthorized analysis. Methodology: An experimental quantitative approach was conducted through the development of a Python-based desktop application. Ten test images (RGB and grayscale) with varying resolutions were encrypted and decrypted using predefined key settings. Security and performance were evaluated using histogram analysis, entropy, pixel correlation, key sensitivity, processing time, and key space. Findings: The encrypted images exhibit near-uniform histograms, entropy values approaching the ideal for 8-bit images (≈8), and pixel correlation values close to zero, indicating strong statistical concealment. The scheme also demonstrates high key sensitivity, where small key changes prevent meaningful decryption, and a large key space that supports brute-force resistance. Processing time increases with image size but remains practically feasible for desktop implementation. Implications: The proposed scheme can be applied to protect sensitive image data in local desktop environments and image exchange scenarios, reducing risks of statistical attacks and brute-force attempts while maintaining acceptable runtime for common image sizes. Originality: This study delivers an end-to-end integration of Arnold’s Cat Map and the Duffing Map within a permutation–diffusion structure implemented as a Python desktop application, supported by structured security and efficiency evaluation, thereby providing a practical and reproducible contribution to chaos-based image cryptography.
Implementation of Machine Learning for Freshwater Fish Detection
Recent advancements in mobile technology and machine learning have enabled the development of practical tools, such as Android applications, to assist in real-time fish species identification, particularly in the context of freshwater fisheries in Indonesia. Objective: This research aims to design and implement an Android application that helps anglers accurately identify and categorize freshwater fish species native to Indonesia. The app integrates machine learning-based image recognition to provide a practical tool for fishing enthusiasts while supporting conservation efforts for Indonesia’s freshwater biodiversity. Methodology: A quantitative approach was employed, focusing on mobile application development using Kotlin for Android. The application uses a TensorFlow Lite-based image recognition model for real-time image processing on mobile devices. Data for the model were gathered from publicly available fish species datasets. The system was tested across multiple Android devices to evaluate compatibility and efficiency. Findings: The application successfully identifies and classifies various freshwater fish species in Indonesia, providing users with accurate species profiles, biological characteristics, and appropriate bait recommendations. The system operates efficiently in real-time on mobile devices without relying on cloud computing, ensuring accessibility in remote areas. Testing results across different Android devices confirm the app's robustness and user-friendly interface. Implications: This research demonstrates the integration of mobile technology and machine learning in fisheries, offering a valuable tool for both recreational and professional anglers. The app promotes awareness of freshwater fish species preservation and supports sustainable fishing practices. Additionally, it can serve educational purposes by enhancing knowledge of local biodiversity and fostering fish conservation efforts. Originality: This research introduces an innovative mobile-based solution to freshwater fish identification. Unlike previous studies, which focused on desktop-based methods, this study offers a practical mobile application that operates efficiently in real-time on-site. The originality lies in combining machine learning and mobile technology to address fish identification challenges while contributing to biodiversity conservation.
Evaluation of Continuous Emission Monitoring System (CEMS) Performance and Integration with Data Acquisition and Interfacing Systems for Regulatory Compliance in Indonesia's Industrial Sector
Air pollution from industrial emissions is a critical issue in Indonesia, affecting public health and the environment. Continuous Emission Monitoring Systems (CEMS) are crucial for real-time monitoring and ensuring compliance with environmental regulations. Objective: This study aims to evaluate the performance of the CEMS integrated with the Data Acquisition System (DAS) and Data Interfacing System (DIS), developed by BRIN and PT Eksperta Adi Manusa, to improve emissions monitoring and reporting. Methodology: A case study evaluation with a descriptive-qualitative and observational approach was used. Data was collected through simulations with MODBUS data, system documentation analysis, and performance testing of the dashboard module. The study focused on system architecture, data integration, and compliance with Indonesian environmental regulations. Findings: The integration of CEMS with DAS and DIS successfully enabled real-time monitoring and enhanced emission data accuracy. However, challenges such as data variability and the need for stronger regulatory supervision were identified. The research also found that predictive emission monitoring systems (PEMS) could improve system performance and reduce operational costs. Implications: This research contributes to improving air quality management in Indonesia. The findings highlight the importance of real-time monitoring and system integration for better decision-making and regulatory compliance. The study provides recommendations for policymakers and industry stakeholders to optimize CEMS and PEMS implementation for reducing industrial pollution. Originality: This research provides original insights into CEMS integration within Indonesia’s regulatory framework, a relatively unexplored area. It contributes to the field of environmental monitoring by offering practical recommendations to enhance emission monitoring systems and address challenges faced by industries in complying with regulations.
Optimization of Warehouse Inventory Policy Using ABC–XYZ Analysis and the (Q,R) Model to Reduce Total Inventory Cost and Stockouts
Warehouses are pivotal nodes in supply chains, yet many distribution centers still apply uniform replenishment rules that ignore differences in item value and demand uncertainty. This practice often leads to simultaneous overstock (high holding cost) and stockouts (service failure), reducing overall operational efficiency. Objective: This study aims to optimize finished-goods inventory control in the distribution warehouse of Manufacturing Company X by integrating ABC–XYZ classification with class-based replenishment policies to improve the cost–service trade-off and service reliability. Methodology: The research uses a quantitative applied case-study design. Data were collected from secondary operational records (SKU demand history, lead time, inventory transactions, and cost parameters) and supported by primary inputs through observation and interviews to confirm replenishment constraints and routines. Analysis was conducted by (1) classifying items using ABC (annual usage value) and XYZ (demand variability), (2) translating classes into differentiated service targets and continuous-review policy parameters (order quantity, reorder point, and safety stock), and (3) evaluating performance using a before–after KPI comparison between the baseline and proposed policies. Findings: The results show strong value concentration and heterogeneous demand variability across SKUs, supporting differentiated control. The proposed policy reduces total inventory cost from IDR 8.75 billion to IDR 8.10 billion (−7.4%), decreases stockout incidents from 96 to 52 (−45.8%), and increases service level from 92.4% to 96.1% (+4.0 percentage points). Improvements are most pronounced in high-priority and high-uncertainty groups. Implications: The findings suggest that managers can improve warehouse service reliability while lowering costs by allocating buffers and control intensity according to item priority and uncertainty, supported by periodic class refresh, master-data governance, and inventory record-accuracy improvement (e.g., class-based cycle counting). Originality: This study contributes an end-to-end, implementable pipeline from ABC–XYZ segmentation to differentiated service targets, policy parameterization under practical constraints (e.g., MOQ/pack sizes), and KPI-based validation demonstrating measurable operational benefits beyond classification-only approaches.
Prototype of an IoT-Based Height Sorting Conveyor using ESP32, HC-SR04, and IR Sensors
Abstract: Industrial sorting on small-scale production lines is often still performed manually, which can reduce throughput consistency, increase human error, and limit real-time traceability. Objective: design, implement, and evaluate an ESP32-based conveyor prototype that automatically sorts items by height while providing local and IoT-based monitoring. Methodology: engineering experimental approach (prototype development and verification testing). Data were collected from embedded sensor readings (HC-SR04 ultrasonic and IR sensors), actuator response observations, LCD outputs, IoT dashboard records, and manual reference measurements for validation. Data were analyzed by assessing measurement accuracy, detection reliability, actuator responsiveness, and overall sorting success rate. Findings: HC-SR04 estimated item height with good accuracy (average deviation approximately ±0.1 cm), supported by interrupt-based handling and data averaging to improve stability. IR sensors reliably detected item presence and position, while pull-up configuration and debounce logic prevented duplicate triggering. MG90S 180° servo actuator performed smooth category-based diversion using non-blocking and soft-open control without disrupting other system processes. Sorting success rate exceeded 95%, and operation remained stable in both offline and online modes, with IoT integration enabling real-time monitoring without becoming a dependency for control. Implications: proposed architecture can function as a low-cost learning platform and a basis for small-scale industrial automation requiring reliable sorting and operational visibility. Originality/value: integration of baseline-calibrated ultrasonic height measurement, IR-based position gating, non-blocking servo control, local 20×4 I2C LCD feedback, and IoT monitoring into a single workflow that remains functional during network disruptions.
The Effect of Occupational Health and Safety (OHS) Knowledge and Organizational Commitment on Employees’ Ability to Minimize Workplace Accidents at Hospital X, Surabaya
Workplace accidents remain a critical Occupational Health and Safety (K3/OSH) issue, particularly in hospitals where employees are exposed to multiple hazards and high work intensity. Strengthening employees’ ability to minimize workplace accidents is essential to protect staff, maintain service continuity, and improve organizational performance. In this context, K3/OSH knowledge and organizational commitment are assumed to be key factors supporting accident-prevention capability. Objective: This study aims to analyze the effects of K3/OSH knowledge and organizational commitment on employees’ ability to minimize workplace accidents at Hospital X Surabaya, both simultaneously and partially. Methods: This study employed a quantitative, cross-sectional design. Data were collected using a structured questionnaire administered to 84 employees selected from a population of 179 using Slovin’s formula (e = 0.10). Respondents included clinical and non-clinical staff (doctors, nurses, midwives, medical record officers, pharmacists, radiology staff, and administrative personnel). Data were analyzed using multiple linear regression with SPSS, assessing the overall model significance (F-test) and the partial effects of each predictor (t-tests). Results: The regression model was statistically significant, indicating that K3/OSH knowledge and commitment jointly predict accident-minimization ability (F = 142.686, p < .001). Partially, K3/OSH knowledge had a significant positive effect on accident-minimization ability (t = 4.423, p < .001), and organizational commitment also had a significant positive effect (t = 3.104, p = .003). These results suggest that employees’ ability to minimize workplace accidents tends to increase when they have stronger OSH knowledge and higher commitment. Implications: Hospitals should implement integrated OSH interventions that combine competency development (e.g., role-specific K3 training, SOP reinforcement) with commitment strengthening (e.g., leadership consistency, safety culture reinforcement, supportive supervision) to enhance accident prevention. Originality: This study provides context-specific evidence from an Indonesian hospital by testing K3/OSH knowledge and commitment simultaneously within one predictive model across diverse occupational roles, highlighting the need for combined knowledge–commitment strategies in accident prevention.
Analysis of the Implementation of Green Building Technology in Building Maintenance
Hospitals are resource-intensive facilities with continuous operations that result in high energy and water consumption, making the implementation of green building technology essential to improve environmental performance during the operational phase. Objective: This study aims to identify the energy, water, and material efficiency measures implemented at RSUD dr. Soeratno Gemolong, Sragen, and to evaluate the level of efficiency achieved based on EDGE (Excellence in Design for Greater Efficiencies) standards. Methods: The research employed an applied evaluative approach by collecting primary and secondary data through direct observation, interviews, documentation review (as-built drawings and material data), and literature review. The collected data were analyzed using the EDGE application and compared with EDGE benchmarks and relevant Indonesian regulations. Findings: The results indicate that baseline energy efficiency was 19.85%, slightly below the EDGE minimum requirement of 20%, but increased to 24.09% after targeted improvements such as reducing building envelope air infiltration and improving cooling system efficiency. Water efficiency reached 25.75%, and material efficiency achieved 34%, both exceeding the EDGE minimum standard. Implications: These findings demonstrate that EDGE-based evaluation can support maintenance-driven optimization strategies in hospital buildings and provide practical guidance for facility managers and policymakers in prioritizing high-impact efficiency interventions. Originality/Value: This study provides an integrated empirical assessment of energy, water, and material efficiency (EEM, WEM, MEM) in an operational public hospital, showing how targeted improvements can shift energy performance from near-compliance to compliant status within the EDGE framework.
Comparative Analysis of Classical and Quantum-Inspired Optimization for Net-Zero Emission Power Grid Operation
The transition toward net-zero-emission power grids has become increasingly challenging due to the growing penetration of renewable energy, the integration of energy storage, and the implementation of carbon-control policies. These developments increase the operational complexity of modern power systems and require optimization approaches capable of managing multiple technical and environmental constraints. Objective: This study aims to evaluate and compare the roles of classical optimization and quantum-inspired optimization in supporting the operation of low-carbon power grids under different energy-transition scenarios. Method: This research employed a quantitative approach using scenario-based modeling and simulation. The power-grid model integrated renewable energy sources, battery energy storage, and carbon-control mechanisms. Several transition scenarios were evaluated by varying renewable-energy targets, carbon prices, and emission caps. Comparative analysis was conducted using classical optimization based on Mixed-Integer Linear Programming (MILP) as the global optimum benchmark and quantum-inspired optimization based on simulated annealing as an alternative solution approach. Findings: The results show that classical optimization produces better solution quality and higher computational efficiency than the quantum-inspired approach. However, the quantum-inspired method is still able to generate feasible and stable solutions, particularly under scenarios with high renewable-energy penetration and strict emission constraints. Implications: These findings suggest that quantum-inspired optimization has practical potential as a complementary tool for supporting low-carbon power-grid operation and energy-transition planning, especially in increasingly complex systems. Originality: The novelty of this study lies in the direct comparison between classical and quantum-inspired optimization within a unified low-carbon power-grid simulation framework. The study provides added value by positioning quantum-inspired optimization as a complement, rather than a substitute, to classical optimization in net-zero-emission power-grid transition.
Analysis of Factors Influencing Contractor Profit and Loss in Construction Projects: A Case Study of the Boemi Oemmi Luxury Kost Garut Development
Construction projects often face financial challenges that can lead to contractor profits or losses during project implementation. Factors such as labor productivity, material availability, equipment management, financial conditions, and field conditions may significantly affect contractor financial performance. Therefore, identifying these factors is important to improve project management and reduce financial risks. Objective: This study aims to analyze the factors influencing contractor profits and losses in the Boemi Oemmi Luxury Kost Garut construction project and to identify the most dominant factors as well as the actions implemented to address these factors. Method: This research employed a quantitative descriptive approach. Data were collected through questionnaires distributed to respondents involved in the construction project, including contractors, consultants, and project owners. The sampling technique used was purposive sampling. The collected data were analyzed using descriptive statistical methods, including mean value analysis and the Relative Importance Index, to determine the ranking of factors influencing contractor profits and losses. Findings: The results show that labor factors are the most dominant factor influencing contractor profits and losses in the Boemi Oemmi Luxury Kost Garut development project, while equipment factors have the lowest influence. In terms of the implementation of actions to address these factors, material-related issues were found to be the most highly applied factor, whereas weather-related factors were the least applied. Implications: The findings of this study provide practical implications for construction project stakeholders by emphasizing the importance of improving workforce productivity, strengthening material procurement planning, and enhancing project management strategies to minimize financial risks and improve contractor profitability. Originality: The originality of this study lies in its empirical analysis of contractor profit and loss factors within a specific construction project context using a structured ranking approach through the Relative Importance Index, which provides a systematic evaluation of factors influencing contractor financial performance.
Time and Cost Performance Evaluation Using Earned Value Management in Residential Construction Projects
Construction projects frequently experience discrepancies between planned schedules and actual implementation, resulting in delays and cost inefficiencies. Therefore, effective monitoring is needed to evaluate project performance and maintain alignment with planned time and budget targets. Objective: This study evaluates the time and cost performance of the Hanglekir Residential Housing Development Project using the Earned Value Management (EVM) approach. Methodology: This research employed a mixed-method case study design. Quantitative data were obtained from project documents, including cost budget plans, schedules, and progress reports, while qualitative data were collected through field observations and interviews. Project performance was analyzed using EVM indicators, namely Schedule Variance (SV), Cost Variance (CV), Schedule Performance Index (SPI), Cost Performance Index (CPI), and forecasting indicators such as Estimate at Completion (EAC) and Estimate at Schedule (EAS). Findings: The results indicate that the project experienced schedule delays, as shown by SPI values consistently below 1. However, cost performance was relatively efficient in several periods, reflected by CPI values above 1. Forecasting results show that the final project cost is likely to remain below the initial budget, while the completion time is expected to slightly exceed the planned schedule. Implications: These findings demonstrate the importance of integrated project monitoring to improve time and cost control. Originality: This study provides empirical evidence of the practical application of EVM for evaluating both schedule and cost performance in a residential construction project.
Development of a Sensor-Based Flood Early Warning System with SMS Notification in Urban River Restoration Contexts
Urban river restoration areas that function as public spaces and tourism destinations are increasingly exposed to flood risks due to changing hydrological conditions, urbanization, and limited early warning mechanisms. Objective: This study aims to design and implement an automatic flood early warning system based on water level sensors and SMS notifications in the Tukad Tagtag river restoration area, Denpasar, in order to improve flood risk mitigation and public safety. Methodology: This research employs a qualitative applied approach using the Action Research method, which integrates planning, action, observation, and reflection. Data were collected through field observation, system testing, stakeholder consultation, and document analysis. The analysis was conducted using a descriptive and iterative evaluation approach to assess system performance and improvement. Findings: The system successfully detects water level changes in real time, triggers threshold-based alerts, and delivers SMS notifications effectively. System performance improved after iterative adjustments, particularly in sensor positioning and microcontroller configuration, resulting in enhanced stability and reduced false warnings. Implications: The study demonstrates that simple and accessible technology can support effective flood risk mitigation. The system can be applied by local governments and river managers to enhance preparedness, response time, and safety in urban river environments. Originality: This research contributes a practical model by integrating sensor-based detection, real-time processing, and SMS communication within a river restoration tourism context using an iterative Action Research approach.