Spektrum Industri

The Effects of Intermittent Noise and Whole-Body Vibration on Cognitive Performance

Rahmaniyah Dwi Astuti, Farreleo Adryanna Brilliansyah, Ade Aisyah Arifna Putri — Wed, 29 Apr 2026 00:00:00 +0000

Work environments involving noise and whole-body vibration are known to affect human cognitive performance, particularly selective attention. The aim of this study is to identify and analyse the impact of noise level and whole-body vibration exposure duration on cognitive performance using a controlled laboratory experiment and the Stroop Task. Cognitive performance was measured by total response time and accuracy under two intermittent noise levels (65 dBA and 85 dBA) and two whole-body vibration exposure durations (5 minutes and 10 minutes). Multivariate analysis indicated that intermittent noise significantly reduced response accuracy, while longer whole-body vibration exposure slowed response time. No significant interaction between noise and vibration was observed, suggesting that each factor affects cognition through different mechanisms. This study presents novel empirical evidence on the combined cognitive effects of intermittent noise and whole-body vibration exposure assessed via the Stroop Task, an approach rarely used in prior research. This study contributes to provide a better understanding of how physical environmental stressors influence selective attention in occupational settings. From a scientific perspective, controlling noise intensity and the duration of whole-body vibration exposure are essential to minimise adverse cognitive effects at work. Future research should investigate the long-term and combined effects of exposure under more complex cognitive task conditions.

Designing Accessible Election Voting Booths: An Integrated Approach Using Universal Design, Design Thinking, and Ergonomics

Akh Sokhibi, Budi Cahyo Wibowo, Putri Rahmawati, Salman Alfarisi — Wed, 29 Apr 2026 00:00:00 +0000

Voting booths are one of the mandatory facilities for holding elections. However, currently, voting booths still face access barriers for people with disabilities who use wheelchairs. There is no standardization of voting booths that are easily accessible for all users and this is an urgent need for voting booth designs that are easily accessible for all users. Therefore, this study aims to design accessible voting booths for all users of voting rights. The method used in this study combines universal design approaches, design thinking, and ergonomics. Data collected included anthropometric data for people with disabilities who use wheelchairs, user need data for universal design-based voting booth designs, and user experience interview data for the empathy stage in design thinking. Data analysis used normality tests, uniformity tests, and adequacy tests for anthropometric data. On user need data, descriptive tests, level categorization and qualitative interpretation were conducted. Then, design thinking stages were carried out until design evaluation. The results of the study obtained an accessible voting booth design with dimensions of 70 cm leg room height; 75.5 cm lower table layer height; 93.2 cm upper table layer height; 92.9 table length; 55 cm table width and 55 cm booth cover height. The contribution of the study is expected to be an accessible voting booth design based on universal design, design thinking and ergonomics to become a technical guideline for the Indonesian general election commission to accommodate voter rights without discrimination.

Effects of Ergonomic Intervention on Musculoskeletal Complaints and Fatigue in the Abaca Banana Fibre Carpet Industry

Heri Setiawan, Tri Budiyanto — Wed, 29 Apr 2026 00:00:00 +0000

Traditional fibre-based craft industries contribute substantially to employment and community welfare, yet their highly manual production processes often expose workers to significant ergonomic hazards. In the Abaca banana fibre carpet industry, tasks such as fibre extraction, cleaning, drying, sorting, spinning, weaving, and finishing require repetitive movements, prolonged awkward postures, and sustained physical effort, thereby increasing the risk of musculoskeletal complaints and work-related fatigue. This study evaluated the effects of ergonomic intervention on musculoskeletal complaints and fatigue among workers in this industry. This intervention study included 152 workers selected through stratified random sampling and grouped according to the principal production stages. Ergonomic risk was evaluated using the Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA), musculoskeletal complaints were assessed using the Nordic Body Map (NBM), and fatigue was measured using the Borg Rating of Perceived Exertion scale. Assessments were performed one month before the intervention and repeated at follow-up after the intervention. At baseline, workers demonstrated moderate-to-high ergonomic risk, with mean RULA scores ranging from 4.6 to 4.9 and mean REBA scores ranging from 5.2 to 5.6. Musculoskeletal complaints and fatigue were also reported at moderate levels, with mean NBM scores ranging from 43.4 to 47.6 and mean Borg scores ranging from 10.9 to 11.2. Post-intervention analysis showed significant reductions in all outcome measures (p < 0.05), indicating improvements in ergonomic risk exposure, musculoskeletal complaints, and perceived fatigue across production stages. The findings suggest that ergonomic intervention is an effective approach for improving worker health in traditional craft-based industries. Integrating ergonomic measures into manual production systems may help reduce physical burden, enhance occupational well-being, and support sustainable productivity.

Barriers to Green Manufacturing Implementation: A Systematic Literature Review of Internal and External Challenges.

Ajib Haryanto, Irawan Sukma, Agus Darmawan — Wed, 29 Apr 2026 00:00:00 +0000

Green manufacturing has emerged as a strategic response to escalating concerns over industrial pollution, resource depletion, and climate change, yet its implementation remains limited, particularly in developing economies. Manufacturing firms face a dual pressure to sustain competitiveness while reducing environmental impacts, creating trade-offs between short-term economic objectives and long-term sustainability goals. This study responds to that problem by conducting a systematic review of recent research to identify the main internal and external barriers that hinder the adoption of green manufacturing practices. The review aims to provide a structured understanding of these challenges as a basis for more effective managerial and policy interventions. The primary contribution of this paper is an updated synthesis of ten key barriers to green manufacturing, grouped into internal and external categories and derived from high-quality journal publications between 2020 and 2025. Methodologically, this research adopts a three-phase systematic literature review. First, articles were collected from ScienceDirect, SCOPUS, IEEE, and Emerald using general and specific keywords for the period January 2020–October 2025, generating a large initial dataset. Second, the dataset was refined using journal-quality criteria (SJR > 1.0), duplicate removal, and relevance screening at abstract and full-text levels, resulting in 47 core articles. Third, content analysis combining qualitative interpretation and simple quantitative aggregation was applied to identify and interpret barrier-related themes. The results indicate ten dominant barriers, including weak sustainability-oriented culture, limited knowledge and training, high initial and operational costs, insufficient R&D and technology, lack of skilled human resources, limited managerial commitment, inadequate government support, ineffective supply chain management, and low customer awareness and demand. These interacting barriers particularly constrain small and medium-sized enterprises, thereby slowing the wider diffusion of green manufacturing despite its demonstrated environmental and economic benefits.

Optimization of 2200 WP Solar Power Components for EV Charging Using SMART Method

Wed, 29 Apr 2026 00:00:00 +0000

The performance, efficiency, and lifetime of off-grid photovoltaic (PV) systems are strongly influenced by the appropriate selection of key components, including solar panels, charge controllers, batteries, and inverters. This study aims to determine the optimal configuration of a 2200 Wp off-grid PV system for an electric vehicle charging station at Bandung Polytechnic of Manufacturing (Polman Bandung). A Decision Support System based on the Simple Multi-Attribute Rating Technique (SMART) was employed to evaluate multiple technical and functional criteria across several component alternatives. A total of 8 alternatives, consisting of 2 alternatives for each component, were quantitatively assessed using weighted criteria and preference scores to obtain a final ranking. The results indicate that the optimal configuration consists of monocrystalline solar panels, an MPPT charge controller, LiFePO4 batteries, and a pure sine wave inverter, achieving the highest overall utility value. The system produced an output of approximately 1300 W, corresponding to about 59% of the installed capacity (2200 Wp), which reflects the system performance ratio under real operating conditions rather than the intrinsic efficiency of the PV modules. This study contributes to the selection of appropriate components that significantly improve the efficiency, reliability, and operational performance of the system. In conclusion, the SMART-based DSS effectively identifies the optimal components for a 2200 Wp off-grid solar power system, providing a practical and robust solution for electric vehicle charging under varying environmental conditions while ensuring improved efficiency, reliability, and system lifetime.

Supply Chain Optimization through the Implementation of Lean Manufacturing in the Manufacturing Industry

Semuel Pajala, Rusdiaman Rauf, Eric Alan Jones — Wed, 29 Apr 2026 00:00:00 +0000

Manufacturing companies in emerging economies are increasingly challenged to improve supply chain performance amid rising competition, cost pressures, and demand uncertainty. Lean manufacturing improves operational efficiency, but studies integrating performance evaluation and predictive analytics in Indonesian manufacturing remain limited. This study aims to analyze the impact of lean manufacturing implementation on supply chain performance and to develop machine learning–based models for predicting productivity improvement. An explanatory research design using a before, after (pre–post) approach was employed. Data were collected from ten manufacturing firms in South Sulawesi, Indonesia. Supply chain performance indicators, including lead time, productivity, defect rate, and customer satisfaction, were evaluated using paired sample t-tests. In addition, several machine learning algorithms, namely Linear Regression, Support Vector Regression, Random Forest, and Gradient Boosting, were applied to predict productivity outcomes. The findings show that lean manufacturing implementation significantly improves supply chain performance, particularly in reducing lead time and defect rates while increasing productivity. Among the tested models, ensemble-based algorithms, especially Random Forest and Gradient Boosting, exhibited superior predictive accuracy and robustness compared to single-model approaches. The study concludes that lean manufacturing operates as an integrated management system rather than merely a set of operational tools. Theoretically, this research integrates Lean Theory and the Resource-Based View (RBV) with predictive analytics, enriching the lean manufacturing literature. Practically, the results contribute to provide managers with data-driven insights to support sustainable performance improvement and informed decision-making in manufacturing supply chains.

Determining Business Strategies to Increase Sales Using SWOT and QSPM Methods in Furniture Industry

Zain Amarta, Niki Etruly, Juliasari Prasetya, Galih Prakoso — Wed, 29 Apr 2026 00:00:00 +0000

The company under study is a furniture manufacturer that provides various furniture products. Currently, promotional activities are minimal, which necessitates the implementation of effective marketing strategies to promote its products. The aim of this study is to identify appropriate alternative marketing strategies to assess the company’s potential and enhance its capabilities to reach a broader market. The methods used in this research are SWOT and QSPM. Data processing will be conducted using the IFE and EFE matrices. Based on the calculations, the IFE score obtained is 2.894, and the EFE score is 3.0375. According to these scores, the company is positioned in cell II (grow and build). Based on the SWOT and QSPM results, the recommended strategies to enhance marketing are: increasing the number of sales teams to reach a wider market with a score of 10, enhancing promotional activities to expand market reach with a score of 8.1, and participating in exhibitions to introduce products and the company to the public with a score of 8.

Behavioral Responses of Nonsmokers to Environmental Tobacco Smoke Exposure

Desrina Yusi Irawati, Nyoman Sri Widari, Armadeo Ruben Canariesa — Wed, 29 Apr 2026 00:00:00 +0000

Second-hand smoke (SHS) exposure remains a significant public health issue among Indonesian adolescents, particularly in areas where smoking is socially accepted and smoke-free regulations are weakly enforced. However, limited research explains the psychosocial mechanisms shaping protective intentions among adolescent passive smokers in non-metropolitan settings. This study examines the determinants of protective behavioral intention and actual SHS exposure by extending the Theory of Planned Behavior (TPB) with additional cognitive, emotional, and environmental constructs. By incorporating risk perception, emotional responses, psychological reactions, negative cognition, and environmental exposure, the study offers a context-sensitive behavioral framework for SHS in high-exposure environments. Data were collected through a survey of 140 adolescent non-smokers in Tanjung Selor, Indonesia, who were routinely exposed to cigarette smoke. The model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that emotional responses (Beta = 0.399, p < 0.001) and environmental exposure (Beta = 0.401, p < 0.001) significantly predict protective behavioral intention, whereas the classical TPB constructs show limited explanatory power. Risk perception exerts strong indirect effects through emotional responses (Beta = 0.678, p < 0.001) rather than directly influencing intention. Behavioral intention strongly predicts actual SHS exposure (Beta = 0.507, p < 0.001). These findings indicate that adolescents’ protective intentions are shaped more by affective and environmental factors than by rational evaluations alone. This study contributes to provide study extends TPB in SHS research and provides empirical guidance for emotion-driven and environment-focused tobacco control interventions in non-metropolitan regions.

The Role of Sustainability in Innovation Networks to Enhance SME Competitiveness: An Integrative Framework Based on PRISMA and Bibliometric Mapping

Ragil Pardiyono, Parwadi Moengin, Kadarsah Suryadi, Dian Mardi Safitri — Wed, 29 Apr 2026 00:00:00 +0000

Small and medium-sized enterprises (SMEs) play a critical role in economic development; however, their competitiveness remains constrained by fragmented integration of sustainability and innovation practices. Previous studies examine direct relationships between sustainability and competitiveness, without sufficiently explaining how innovation networks and policy environments interact within this relationship. This study addresses this gap by developing an integrative understanding of the role of sustainability in innovation networks to enhance SME competitiveness. This research employs a Systematic Literature Review (SLR) based on PRISMA 2020 guidelines, combined with bibliometric analysis using VOS viewer. The literature search initially identified 5,393 articles from the ScienceDirect database, of which 59 met the inclusion criteria for final analysis. The results reveal four main thematic clusters: (1) sustainability-oriented innovation, (2) internal firm capabilities, (3) innovation networks and national innovation systems, and (4) policy and digital transformation. The findings indicate that SME competitiveness emerges from the interaction between internal capabilities, collaborative networks, and institutional support, with sustainability acting as both a driver and outcome of innovation processes. This study contributes theoretically by proposing an integrative framework that extends prior literature by incorporating innovation networks as mediating factors and policy digital environments as enabling mechanisms. Methodologically, it demonstrates the value of combining PRISMA-based SLR with bibliometric mapping to systematically identify research patterns and gaps. Practically, the findings suggest that strengthening sustainability-oriented innovation and innovation networks, supported by appropriate policy and digital infrastructure, may enhance SME competitiveness in the evolving green and digital economy.

Six Sigma-Based Quality Management Strategy to Enhance the Competitiveness of Food Souvenir MSMEs in East Kalimantan

Alex Kisanjani, Marulan Andivas, Hirwandi — Wed, 29 Apr 2026 00:00:00 +0000

Micro, Small, and Medium Enterprises (MSMEs) plays an important role in the Indonesian economy. MSMEs contribute around 60% to the Gross Domestic Product (GDP) and absorb more than 97% of the workforce. The culinary sector, especially local specialty culinary products, is one of the fastest-growing sectors and has great potential to boost the local economy, including in East Kalimantan. However, this potential is not fully realized because many MSMEs still face issues with product quality. This condition reduces MSMEs' market competitiveness. This research aims to develop a strategy to improve MSME quality by prioritizing key areas. The method used is Six Sigma, with the stages of Define, Measure, Analyze, Improve, and Control (DMAIC), combined with Importance-Performance Analysis (IPA). Data collection is conducted through a customer satisfaction questionnaire, which is then analyzed using Six Sigma methods to determine performance levels. The findings indicate that the sigma level of food souvenir MSMEs in East Kalimantan is 2.435. This figure suggests that the process capability in meeting customer expectations remains low. The Importance-Performance Analysis (IPA) identified three priority attributes for improvement: staff appearance, communication with customers, and the provision of product testers. The proposed improvement recommendations are complemented by Key Performance Indicators (KPIs) to ensure the sustainability of quality enhancement efforts. The novelty of this study lies in applying the Six Sigma method to small-scale culinary MSMEs through a multidimensional approach that integrates product quality, service quality, pricing, and customer experience within the context of a developing region. In practice, this study contributes to offer measurable improvement priorities for MSME practitioners, thereby supporting the enhancement of MSME competitiveness at both the local and national levels.

Halal Blood Supply Chain Analysis Using the House of Risk Method

Nisrina Faiza Mufid, Agus Mansur, Rajiv Noor Said, Norhidaya Binti Paozi — Wed, 29 Apr 2026 00:00:00 +0000

The absence of halal assurance mechanisms in blood donation systems presents an urgent challenge in ensuring both medical safety and halal compliance within the blood supply chain (BSC), particularly in Indonesia where over 87% of the population is Muslim. The lack of official halal certification for blood donation poses risks to religious integrity and public trust. Issues such as uncertified materials, inadequate handling supervision, and potential mixing of non-halal blood emphasize the need for a systematic approach integrating medical safety and halal assurance in BSC management. This study contributes theoretically by introducing the concept of a halal blood supply chain and establishing a structured framework for managing halal-related risks in blood donation through the integration of the House of Risk (HOR) model and the Supply Chain Operations Reference (SCOR) framework. Practically, this study offers a risk-based decision support tool for blood service institutions by identifying key halal-related risks and actionable mitigation strategies. Empirically, this research employed the HOR–SCOR framework to identify, assess, and prioritize potential sources of non-halalness in the blood donation operations of PMI Sleman Regency. Data were collected through interviews, observations, and expert validation. The analysis covered 28 risk events and 35 risk agents, quantified using the Aggregate Risk Potential (ARP) and Effectiveness-to-Difficulty (ETD) ratios to determine the most critical risks and appropriate mitigation actions. The results identified four major risk sources: the absence of written halal blood criteria, improper storage temperature, misinterpretation of test results, and machine errors in the crossmatching process. The findings indicate that applying the HOR framework effectively reduces halal-related risks while enhancing operational reliability, transparency, and Shariah compliance within blood donation systems. Furthermore, this study provides a foundation for developing a national halal BSC model and certification system in collaboration with relevant authorities such as BPJPH and MUI.

Developing Traditional Food Supply Chains to Support Food Independence and Security: NRBV, MICMAC and ISM Approaches

Lukman Achmad, Aryo Sahid Sujiwo — Wed, 29 Apr 2026 00:00:00 +0000

Traditional food SMEs play a crucial role in driving the economy, preserving cultural heritage, and supporting food security. However, they face numerous challenges in building sustainable supply chains, including limited knowledge of the roadmap for developing them. This study aims to develop a conceptual hierarchy model that can guide traditional food SMEs in developing a Natural Resources-based View (NRBV)-based supply chain. This study employed a mixed-methods survey to collect and analyze data to answer the research questions. The surveyed companies were eight traditional food processing companies in West Bandung Regency, West Java Province. The study involved 12 expert respondents and 64 consumers as data sources, and employed the Delphi process, MICMAC, and Interpretative Structural Modeling (ISM) as data analysis methods. The analysis identified 13 key success factors relevant to developing an NRBV-based supply chain for traditional food SMEs. Of these factors, four factors categorized as dependent factors (association/professional support, green financing, raw material management, logistics system, and consumer development), three factors categorized as connecting factors (human resource quality, supplier development and environmentally friendly packaging), and five factors categorized as independent factors (information technology implementation, green technology adoption, government policies and support, company leadership commitment, and pollution prevention and waste management). The results of the study provide implications for the importance of waste management, product management, and sustainability in building a sustainable supply chain in traditional food SMEs.

Sustainability Risk Analysis of the Halal Feed Supply Chain for Ruminant Commodities Through the Integration of the SCOR-FMEA Method

Wed, 29 Apr 2026 00:00:00 +0000

Ruminant commodities play a strategic role in maintaining the stability of meat and milk supply for society. In this context, feed serves not only as a key determinant of livestock productivity but also as a critical foundation for environmental sustainability and compliance with halal standards throughout the supply chain. This study aims to map and priorities risks in the ruminant feed supply chain through the integration of the SCOR and FMEA methods. The novelty of this research lies in the integration of sustainability risks with halal-related risks within the supply chain framework. The study was conducted in Gendro Village, Pasuruan Regency. Data were collected through expert assessments of severity, occurrence, and detection levels, taking into account economic, environmental, and socio-halal aspects. The SCOR framework was applied to systematically map sustainability and halal risks along the supply chain, while FMEA was used to determine risk priorities based on the Risk Priority Number (RPN). The findings indicate that the highest RPN values occur in the planning process, particularly in traceability system planning (R5), and in the production process related to product tracking and record-keeping activities (R20). In addition, the study reveals several halal compliances risks that are difficult to detect, including document verification, segregation practices, and line clearance procedures. In practical terms, the identified risk priorities and proposed improvements can be directly implemented by farmers, enabling improvements in feed quality, reductions in losses, preservation of halal integrity, and enhancement of supply chain resilience through realistic and low-cost interventions. Overall, this study contributes a risk prioritization model that integrates economic, environmental, and halal dimensions and links mitigation actions to SCOR processes, making it applicable to ruminant feed supply chains as well as other commodity-based supply chains.

Soft Systems Methodology as a Conceptual Framework for Vehicle Routing Problem

Tombak Gapura Bhagya, Rahmi Maulidya, Parwadi Moengin, Sally Cahyati — Wed, 29 Apr 2026 00:00:00 +0000

Indonesia’s archipelagic geography and uneven infrastructure pose persistent challenges to the distribution of subsidized fertilizer, a strategic commodity critical to national food security. While Vehicle Routing Problem (VRP) models are widely applied to improve logistical efficiency, existing studies predominantly focus on algorithmic optimization and pay limited attention to policy constraints, stakeholder complexity, and service trade-offs in regulated distribution systems. This study addresses this limitation by developing a conceptual VRP framework grounded in Soft Systems Methodology (SSM), positioning fertilizer distribution as a policy-constrained socio-technical system. The research follows Check land’s seven-stage SSM process, moving from unstructured problem exploration to the identification of feasible and desirable changes. Supporting tools include VOSviewer for literature mapping, Rich Pictures for stakeholder representation, CATWOE for system definition, and Causal Loop Diagrams (CLD) to capture dynamic interdependencies. The analysis of a multi-echelon distribution network demonstrates that inefficiencies arise not merely from routing limitations but from structural misalignment among routing efficiency, service capacity, inventory control, and government subsidy ceilings. A key insight is the inherent trade-off between cost minimization and service responsiveness in subsidized logistics systems. The study contributes theoretically by reframing VRP within systems thinking, methodologically by integrating qualitative structuring with optimization design, and practically by offering a reusable framework for transparent and policy-responsive public logistics management.