Jurnal Optimasi Sistem Industri

A Multi-Objective Double Row Layout Problem Considering Safety Distances and Geometrical Constraints

Achmad Pratama Rifai — 2025-12-31

This study addresses an enhanced version of the Double Row Layout Problem (DRLP) by incorporating two critical constraints: minimum safety distances between machines and geometric limitations on row lengths. A bi-objective mixed-integer non-linear programming (MINLP) model is formulated to simultaneously minimize material handling costs and penalties for violating safety distance requirements. To solve the problem efficiently, a novel metaheuristic called Improved Multi-Objective Variable Neighborhood Search (IMOVNS) is proposed. IMOVNS extends the standard MOVNS by integrating an adaptive archive update strategy and a probabilistic acceptance mechanism inspired by AMOSA, thereby improving both convergence and diversity in Pareto front generation. This study contributes to the layout optimization literature by proposing a tailored MOVNS variant explicitly designed for safety-aware and geometry-constrained DRLP, a challenging problem variant that has received limited attention in prior research. Extensive experiments on 27 DRLP instances show that IMOVNS demonstrates strong performance, significantly outperforming NSGA-II and showing competitive or superior results compared to AMOSA and MOVNS in terms of convergence and solution diversity. Statistical tests further confirm the significant superiority of IMOVNS, particularly over NSGA-II. Additionally, a key managerial insight reveals that layouts with unbalanced row lengths favour safety compliance, while balanced layouts minimize material handling costs. The Pareto-optimal solutions generated by IMOVNS enable decision-makers to select layout configurations that align with specific operational priorities. These findings highlight the practical relevance and robustness of IMOVNS in solving real-world multi-objective facility layout problems under complex spatial and safety constraints.

Consumer Insights for Optimization of Industrial Systems: The Case of Consumers’ Greenwashing Perception in Adopting Single-Use Plastics Products in Padang City

Hafiz Rahman — 2025-12-31

This study explicates the impact of consumer perceptions of greenwashing on the purchase intentions of single-use plastic products, specifically bottled still water and soft drinks, within the context of growing sustainability concerns. The objective is to understand how these perceptions influence consumer decisions and how the insights can inform the optimization of industrial practices related to packaging and marketing. Using a quantitative explanatory design, data was collected from no less than one hundred and sixty-eight respondents in Padang City through direct and online surveys. The sampling method is the Non-Probability Sampling method with a Purposive Sampling approach and it is directed to individuals who meet the following criteria: (1) minimum age of 17 years old; (2) domicile in Padang City; and (3) individuals or households who know bottled water and soft drinks brand. The data analysis, conducted via Structural Equation Modelling (SEM) using SmartPLS, reveals that negative perceptions of greenwashing significantly reduce purchase intentions. However, positive word-of-mouth can mitigate these effects, leading to a higher likelihood of purchase. The findings highlight the critical role of environmental awareness in shaping consumer behavior and suggest that companies should prioritize authentic sustainability practices which could be in terms of third-party certification to maintain consumer trust and optimize their product strategies. Companies are expected to be able to do business responsibly, by paying attention to the end-to-end production process that has minimal waste and minimal impact on the environment, through the development of more environmentally friendly products and optimization of waste management programs. Third-party certifications may be useful to support this effort.

Mixed Methods Approach to Ergonomic Risk Assessment in Malaysian Railway Maintenance Operations

Hellstrome Young Akuma — 2025-12-31

The safety and well-being of human personnel play an increasingly important role in determining whether prescribed objectives and overall performance goals are met in work environments. Various Ergonomic Risk Assessment (ERA) methodologies are thus constantly applied to examine whether risks and hazards that can lead to musculoskeletal disorders (MSDs) are present in these environments. This is especially true in high-risk industries, such as railway maintenance, where workers are subjected to repetitive tasks that are often dynamic and complex in nature. This study, therefore, proposes a conceptual framework to assess ergonomic risk factors (ERFs) in such environments, and suggests mechanisms for intervention. To achieve this, a Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) was used to collect pain and discomfort data from 27 Malaysian railway maintenance workers (n=27). This was supported by semi-structured interviews, which provided context for the numerical results and incorporated workers’ perceptions of their routine tasks into the overall study design. Findings from the collected data showed that workers were often exposed to ERFs, including awkward and static postures over long periods of time. Pain and discomfort were also reported in upper body regions, including the shoulders, neck, and wrists. These results exposed the need for the incorporation of modern technological tools to support the assessment process. The proposed framework, therefore, sets a stage for the integration of Three-Dimensional Computer-Aided Design (3D-CAD) and Virtual Reality (VR) as simulation and visualization components of ERA.

Design of Luxury Train Seat Integrating Emotional Perception and Local Wisdom Approaches

Afif Hakim — 2025-12-31

Although the physical ergonomics of seat design have been extensively studied, emotional comfort is still largely overlooked, especially in public transport. This study addresses this gap by incorporating passengers' emotional perceptions into the design of luxury train seats, in response to documented user discomfort which transcends physical dimensions. The aim was to design seats based on the emotional needs of users and the principles of Kansei engineering, incorporating elements of Javanese cultural values as a form of local wisdom. Emotional responses were captured using Kansei words derived from user interviews, online reviews, and from the expertise of local practitioners. The designs included batik and Javanese decorations. A statistical analysis using Quantitative Theory of Type I (QTT1) identified design elements corresponding to semantic differences between Kansei words. Analysis revealed that the dominant emotional dimension is creative, as indicated by the highest multiple of R-squared 0.9785. This dimension has been operationalized in 14 concrete design elements of the proposed seating concept. The innovative use of batik motifs on the seat backrests was a distinctive feature and underlined the fact that users perceived cultural integration as central to the creative dimension. The study concluded that the integration of emotional perception, represented by the creative dimension, and local wisdom, represented by the batik elements, is a viable strategy for the design of culturally distinct and emotionally attractive luxury train seats. It shows that the culturally rooted approach of Kansei Engineering contributes to the welfare of users.

Acceptance and Satisfaction of Food Waste Mobile Application in a Developing Country: Insights from Extended UTAUT2 and IPMA

Ari Widyanti — 2025-12-31

Food waste is a major global problem and has prompted the development of digital solutions such as food waste mobile applications (FWMA). However, factors influencing the user adoption of these applications, especially in developing countries, remain unexplored. The purpose of this study is to analyze existing behavior towards FWMA and modeling factors that influence acceptance of FWMA in the developing country - Indonesia, while also observing efforts to improve its effectiveness and user satisfaction. To achieve this, an acceptance model is developed using the Extended Unified Acceptance and Use Theory 2 (UTAUT2 Extended) model. Moreover, the Importance-Performance Matrix Analysis (IPMA) framework is used to identify areas for improvement and prioritize efforts to increase customer satisfaction in the application of the FWMA. A preliminary sample of 79 respondents completed an online questionnaire consisting of 30 questions and using a five-point Likert scale with anchor values of strongly agree and strongly disagree. The results show that the average frequency of purchases made by respondents via the FWMA system is relatively low, i.e., three or less per month, and that the majority of respondents learnt about the FWMA system from social media and their friends. As far as demographic data is concerned, women are more likely to use the FWMA than men. In particular, according to the UTAUT2 Extended Model, factors influencing satisfaction with the use of FWMA include social influence, habit and trust; furthermore, satisfaction and different food choices influence the intention to use the use of FWMA. Finally, the IPMA results reinforce the focus on increasing satisfaction through diversified food choices by providing a framework for developers and policy makers to support the uptake of the FWMA in developing economies by building trust, promoting habits and strategically increasing food diversity.

Determining the Number of Stops and Recharging Time for Electric Vehicle Trips Using GIS and k-Means Clustering

Arielle Elias Arantes — 2025-12-31

The increasing adoption of electric vehicles (EVs) worldwide is driven by environmental concerns and the depletion of fossil fuels. Yet, the limited battery range remains a significant barrier to their widespread use, particularly for long-distance travel. This study addresses this challenge by developing a methodology to determine the number of recharging stops, their durations, and strategic locations for electric vehicle charging stations (EVCSs) using k-means clustering analysis, with proposed station locations visualized within a GIS framework. The method integrates quantitative data from questionnaires administered to transportation experts and professionals (N=24) and applies it to case studies across three major highway routes in Ceará, Brazil. The k-means clustering proposed a solution of three stops with a 28-minute recharge time; however, subsequent analysis revealed this time was an overestimate compared to a more precise, distance-based linear model. A key implication is that while clustering can group user preferences, its direct output for operational parameters like charging time can be imprecise. Therefore, we demonstrate the necessity of calibrating such models with physically-grounded equations to achieve practical and efficient trip planning. This approach highlights the importance of integrating user preference data with distance-based models to create more realistic EV infrastructure plans for long-distance corridors.

Factors Affecting Personal Hearing Protector (PHP) Use Among Industrial Workers: Development and Validation of the Questionnaire

Nur Syafiqah Fauzan — 2025-12-31

Personal hearing protectors (PHPs) used by industrial workers have already been a preferred measure in various industrial sectors that have issues with excessive noise exposure. Although personal hearing protectors (PHPs) are widely provided across industrial workplaces, actual worker compliance with their consistent and correct use remains notably low. Therefore, this study aimed to develop a valid measure to evaluate factors affecting PHP use among industrial workers in Malaysia. A questionnaire was developed on the factors affecting PHP use among industrial workers in Malaysia. The questionnaire comprised several items and was created using a systematic, thorough process consisting of three stages: (i) formulating items, (ii) translating them back-to-back, and (iii) subjecting them to expert content assessment by six (6) panels of experts. The questionnaire constructs and items were evaluated for content validity and reliability. The content validity score for each item was considered satisfactory. The Cronbach’s alpha was 0.940, indicating high overall internal consistency. The domain coefficients were as follows: interpersonal influence, 0.899; perceived severity, 0.902; perceived benefit, 0.868; perceived barrier, 0.893; perceived self-efficacy, 0.879; cues to action, 0.815; and use of PHP, 0.840. The domain coefficients demonstrated good to high internal consistency, ranging from 0.815 (cues to action) to 0.902 (perceived severity). This study shows that the questionnaire on factors affecting PHP use among industrial workers is valid and well-structured. Therefore, this study provides a valid and reliable tool for assessing factors influencing PHP use, which can inform the planning of targeted noise management programs.

Cognitive Load Assessment in Multitasking: An fNIRS Study of Prefrontal Cortex Activation for Ergonomic Insight

Ridwan Aji Budi Prasetyo — 2025-12-31

Although traditional neuroimaging techniques like fMRI and EEG have yielded insightful results, their rigid movement limitations restrict their practical use. Functional near-infrared spectroscopy (fNIRS) offers a practical alternative by allowing researchers to measure cortical activity during more natural task performance, particularly in the prefrontal cortex (PFC)—a key region for attention and executive control. This study uses fNIRS to investigate how multitasking demands affect PFC activation. An eight-channel fNIRS system recorded the brain activity of thirty participants as they completed tasks from the Multi-Attribute Task Battery (MATB). Oxygenated hemoglobin (HbO) signals were the main focus of data preprocessing, and AtlasViewer was used to visualize cortical projections. The superior and middle frontal gyri, which are linked to the dorsolateral prefrontal cortex (dlPFC), showed a significant increase in HbO responses when multitasking. On the other hand, lower activation levels were produced under less demanding circumstances. These results are consistent with resource-based models of attention, which postulate that the brain allocates more cognitive resources, especially in the right PFC, as task complexity increases. Beyond theoretical ramifications, this study shows that fNIRS can be used to detect cognitive load in real time. In high-stakes settings like aviation, healthcare, and mission-critical operations, this capability has potential uses in adaptive systems intended to monitor and reduce mental overload. This study emphasizes fNIRS as a useful tool for comprehending and managing multitasking in today's dynamic work contexts by bridging laboratory research and real-world settings.

Goal Programming and Monte Carlo Simulation for Optimizing Inbound Scheduling in Resource-Constrained Warehouses

Savio Enoson — 2025-12-31

Resource efficiency lies at the heart of logistics performance, with unloading operations in storage facilities serving as a critical determinant of overall productivity. In less developed regions, the widespread reliance on basic rules-based systems such as FIFO often proves inadequate for handling operational complexities, leading to bottlenecks and inefficiencies. Small and medium-sized enterprises (SMEs), constrained by limited resources, are compelled to optimize existing infrastructure rather than invest in costly upgrades. To address this challenge, the present study introduces a goal-oriented programming model designed to assign trucks to loading docks within specific time slots, thereby enhancing time efficiency. The model evaluates performance across four key metrics: waiting time, loading time, overtime, and equity. By leveraging goal programming, numerical prioritization of these objectives becomes possible, enabling flexible adjustments to meet operational needs. Furthermore, Monte Carlo simulation (MCS) is employed to incorporate variability into the dataset and assess model robustness under real-world uncertainty. Experimental results reveal that the proposed approach consistently outperforms traditional systems, delivering significant improvements in time efficiency. These findings highlight the potential of goal programming as a practical solution for planning in resource-constrained environments. The resulting model offers an adaptive, reliable framework that warehouse managers can implement without incurring substantial infrastructure costs.

Biomechanical and Perceived Comfort Analysis of FDM 3D-Printed Insoles for Flatfoot Treatment: A Systematic Literature Review

Lina Dianati Fathimahhayati — 2025-12-31

Flatfoot (pes planus), characterized by a reduced or absent medial arch, cause biomechanical disorders, pain and a risk of injury. Customized insoles are a key intervention, with the emergence of 3D printing fused deposition modelling (FDM) based on flexible materials such as thermoplastic polyurethane (TPU) and thermoplastic elastomer (THE). This systematic literature review, based on PRISMA guidelines and analysis of six Scopus studies, assesses the biomechanical and ergonomic properties of these insoles. The results show that flexible 3D printed inserts significantly improve biomechanics by increasing the height of the navicular arch, reducing excessive ankle joint eversion, increasing dorsiflexion and improving the distribution of plantar plate pressure. Regarding perceived comfort, evaluations using the Visual Analog Scale (VAS), the Likert scale and the American Orthopaedic Foot and Ankle Society (AOFAS) questionnaire consistently indicate improved user comfort over no insole or conventional option. Despite these advantages, challenges include limited material options, inconsistent print quality and technical fabrication problems. Further research is needed, especially large-scale studies, to resolve these problems and to improve the clinical use of the product. In conclusion, flexible inserts printed with FDM have the potential to improve both the biomechanical function and the perceived comfort of the footwear use.

Digitalization and Sustainability Indicators for SMI Resilience in Developing Economies: A Conceptual Model from Padang City of Indonesia

Rini Syahfitri — 2025-12-31

The application of digital technology increases productivity, expands market reach, helps small and medium industries (SMIs) adapt to various changes, and provides a great contribution to sustainability. Sustainability emphasizes the importance of maintaining economic, environmental, and social balance in the long term, while resilience describes the ability of SMIs to confront and recover from various disruptions. However, the SMIs in Padang are less aware of the importance of implementing digitalization sustainably to achieve SMI resilience. Several indicators remain unmet by SMIs. This study aims to compile and validate digitalization and sustainability indicators appropriate to the context of local SMIs. These indicators were collected from various literature sources that include digital literacy, digital marketing, economic, environmental, and social sustainability, and resilience aspects. The validation process involved five experts from academia, government, and industry practitioners selected based on their expertise in the fields of the aforementioned aspects. Experts assessed the relevance and clarity of each indicator using the Likert scale, then the results were analyzed with the Aiken index and tested for reliability between assessors using SPSS to ensure consistency of assessments. The results of the study show that these indicators are aligned with the dimensions measured, particularly those that affirm the importance of digital literacy, digital marketing, and social aspects of sustainability in strengthening the resilience of SMIs. These validated indicators were then used to develop a conceptual model that can be a strategic reference for stakeholders and policymakers to increase the competitiveness, resilience, and sustainability of SMIs in Padang.