Spektrum Industri

Prototype Design of Ergo-Flexibility Wheelchair Based on Stakeholder Technical Requirements, Zachman Framework Approach, and Nigel Cross Method Integration

Fri, 31 Oct 2025 00:00:00 +0000

The increasing demand for ergonomic and flexible wheelchairs in Indonesia highlights the need for innovation that meets both user needs and national standards. Most wheelchairs circulating in the domestic market are low-cost imported products that do not comply with the ISO 7176 series SNI 09-4663-1998 medical device standard, leading to concerns over safety and quality assurance. This study aims to design an ergo-flexibility wheelchair prototype based on stakeholder technical requirements while identifying gaps in the existing standards to improve product competitiveness and user protection. The research integrates the Zachman Framework according to the FACTS stages with the Nigel Cross seven-step design method. Data were collected through observation, in-depth interviews, and participatory ergonomics focus group discussions. The data analysis employed the Inter-Rater Reliability (IRR) method to determine stakeholder agreement levels. The findings identified seven key technical parameters, stability, maneuverability, mobility, dimensions, strength, durability, and product information, that are essential for wheelchair standardization. The mapping analysis revealed that the current SNI standard primarily emphasizes product strength through drop testing, while other ergonomic and safety factors remain unaddressed. From the evaluation of three design alternatives, Alternative 2 was selected, featuring aluminum material, dimensions of 1000 mm (L), 620 mm (W), and 910 mm (H), a foldable transport design, semi-manual manufacturing, and a weight of 12 kg with an 80 kg load capacity. Prototype testing using a roll machine and static load confirmed its structural reliability and ergonomic performance. The research contributes to advancing national wheelchair standards by integrating stakeholder-driven design parameters, promoting local innovation, and enhancing the competitiveness of Indonesian medical devices.

Integration of Quality Function Deployment (QFD) and Ergonomic Work Posture Analysis to Redesign the Dyeing Table at Batik Mahkota Laweyan

Fri, 31 Oct 2025 00:00:00 +0000

The traditional batik industry still depends on non-ergonomic tools, especially during the Colet dyeing process, which exposes artisans to significant musculoskeletal disorder (MSD) risks. Prolonged static postures, repetitive arm movements, and mismatched table heights cause discomfort in the back, shoulders, and neck, ultimately reducing productivity. This study aims to design an ergonomic workstation that enhances safety and comfort for batik workers through the integration of the Nordic Body Map (NBM), Rapid Entire Body Assessment (REBA), and Quality Function Deployment (QFD) approaches. Three workers from Batik Mahkota Laweyan participated in the research through questionnaires, observations, and interviews. NBM identified the colet process as the most discomfort-inducing activity, while the initial REBA score of 9 indicated a very high ergonomic risk. The QFD analysis translated workers’ needs into specific technical criteria, such as adjustable height, tiltable surface, and lightweight materials, resulting in a redesigned dyeing table prototype. CATIA simulations validated the improvement, with the REBA score decreasing from 9 to 3, signifying a shift from high to low risk. The findings confirm that integrating ergonomic analysis tools with participatory design effectively reduces MSD risk and supports user-centered innovations in traditional craft industries. The study contributes theoretically by proposing a replicable framework that bridges ergonomic assessment and design application, and practically by providing a validated workstation design that improves comfort, health, and productivity. The novelty lies in the combined use of NBM, REBA, and QFD within a single methodological framework, an approach rarely applied in the traditional batik sector, demonstrating how systematic ergonomic integration can modernize artisanal practices while preserving cultural craftsmanship.

Karakuri Kaizen Design to Reduce Work Time at the Packing Station

Yusuf Mauluddin, Bagas Fardiansyah — Fri, 31 Oct 2025 00:00:00 +0000

This study investigates production bottlenecks at the packing station of PT Anta Boga Pangan Nusantara, where manual operations resulted in prolonged cycle times and reduced efficiency. The research aims to design and implement a Karakuri Kaizen–based Lean Mover to minimize work time and enhance process performance. A quantitative approach was employed, involving direct observation, time measurement, and process analysis. The implementation of the Lean Mover successfully reduced the cycle time from 158.08 seconds to 24.74 seconds, outperforming the target takt time of 27 seconds. These findings demonstrate that low-cost, energy-efficient mechanical systems can effectively eliminate non-value-added activities, balance operator workloads, and improve productivity in food industry operations. The novelty of this study lies in the application of Karakuri Kaizen within the food manufacturing sector, a field rarely explored in previous research, thereby extending its applicability beyond conventional industrial settings. The study contributes theoretically by providing empirical evidence of Karakuri Kaizen’s effectiveness in optimizing manual operations in resource-constrained environments, and practically by offering an ergonomic, sustainable, and affordable alternative to high-cost automation systems.

Weighting the Indoor Environmental Quality on Work Performance

Tranggono, Radityo Anggoro, Muhamad Mukhtarul Haqi, Aldi Pramoedya Nugroho — Fri, 31 Oct 2025 00:00:00 +0000

Poor indoor environmental conditions are often associated with reduced concentration, lower motivation, and decreased productivity in office settings. Addressing this issue requires a systematic assessment of Indoor Environmental Quality (IEQ) and its contribution to work performance. This study examines the effect of Indoor Environmental Quality (IEQ) on office worker performance, focusing on five components: Indoor Air Quality (IAQ), Thermal Comfort, Lighting Quality, Acoustic Quality, and Occupant Experience. The Best-Worst Method (BWM) was applied to determine the relative importance of these factors through a combination of subjective surveys and objective weighting using linear programming. Results indicate that Occupant Experience, particularly ergonomic improvements such as adjustable furniture and optimized layouts, has the strongest influence on productivity. Thermal Comfort ranks second, followed by Lighting Quality, Acoustic Quality, and IAQ. Sensitivity analysis confirms the robustness and consistency of the findings. This research contributes by offering a systematic weighting of IEQ factors, highlighting the central role of ergonomics in workplace design. The study emphasizes that integrating ergonomic and environmental considerations is essential to improve worker performance. The novelty of this study lies in integrating Occupant Experience into the BWM framework, providing a more comprehensive model of IEQ and offering new insights for designing healthier and more productive office environments.

Closing the Loop: Goal Programming-Based Optimization in a Tofu-Centered Agro-Eco-Industrial Park

Fri, 31 Oct 2025 00:00:00 +0000

Developing an agro-eco-industrial park based on the tofu industry must consider the balance of each agro-industry's production capacity. This research aims to (1) develop an optimization model for material flow between industries and (2) explain the material flow and provide waste utilization recommendations for other industries to create a closed loop. The industries involved in this agro-eco-industrial park consist of the tofu industry, fertilizer producers, tempeh gembus producers, cattle farms, biodigesters, paddy farmers, soybean producers, and nata de soya producers. The model was created using a goal programming approach. Traditional tofu processing generally generates a variety of waste with high nutritional value, but it is detrimental to the environment if disposed of directly. The flow of materials among the related industries is based on the tofu industrial cluster, which consists of 30 industries in Grobogan, Central Java, Indonesia. The expected output comprises eight decision variables representing the production amount of industries. Data analysis reveals that the model outperforms the current conditions, with the waste recycling rate increasing from 14 % to 97 %. This model converts waste into valuable resources such as fertilizer and gas energy through biodigester processing and other economically viable methods.

Open Field Layout Problem Using Hybrid Approaches: A Systematic Review

Donny Montreano, Dadan Umar Daihani, Winnie Septiani, Didien Suhardini — Fri, 31 Oct 2025 00:00:00 +0000

The Open Field Layout Problem (OFLP) is a free-configuration layout problem characterized by the absence of floor constraints and an unlimited number of potential solutions. This systematic literature review analyzed over 3,000 Scopus-indexed articles using the keyword "facility layout problem" and related terms, identifying 154 studies that applied hybrid approaches. Terms such as two-stage, multi-stage, or similar variations were classified accordingly. The review revealed that OFLP is not a monolithic concept but comprises five principal types: (1) layouts without aisles or floor boundaries, (2) tightly packed layouts with minimal spacing, (3) layouts with aisles and large residual space, (4) layouts with aisles and floor boundaries, and (5) layouts with aisles but no floor boundaries. The first type is most commonly addressed, while the fifth remains underexplored. This classification highlights a critical research gap and points to opportunities for advancing from low- to high-level hybrid strategies

Determining the International Hub Port on Sumatra Island Using the Integration of Geographic Information System and Analytical Hierarchy Process Methods

Setijadi, Verani Hartati, Muchammad Fauzi, Melati Salma — Fri, 31 Oct 2025 00:00:00 +0000

Indonesia’s maritime trade development heavily depends on the effective utilization of its port infrastructure, particularly in Sumatra, which is strategically located along the Malacca Strait and near major ASEAN markets. However, trade and logistics activities remain concentrated in Java, creating regional imbalances and leaving western Indonesian ports underutilized. This study aims to identify the most strategic ports in Sumatra that can serve as international trade hubs by developing a spatially integrated, multi-criteria evaluation framework. Three main criteria, trade volume, global connectivity, and multimodal accessibility, were assessed using the Analytic Hierarchy Process (AHP) based on expert input from port management, logistics, and transport planning specialists. Geographic Information System (GIS)-based proximity analysis was applied to evaluate each port’s access to roads, railways, and industrial centers, producing a Multimodal Connectivity Index integrated into the AHP model. The findings reveal that Boom Baru (Palembang), Belawan (Medan), and Batu Ampar (Batam) rank as the top-performing ports, with final scores of 0.875, 0.855, and 0.800, respectively. These ports exhibit high trade volumes and superior multimodal connectivity, with Boom Baru and Belawan achieving the highest connectivity index (2.67 out of 3.00). In contrast, Pekanbaru and Tanjung Balai Karimun scored lower due to limited infrastructure and weaker integration. The study concludes that incorporating GIS-based spatial analysis into the AHP framework reduces subjectivity in port evaluation and provides a replicable, data-driven tool for regional infrastructure prioritization. This approach contributes a novel composite index and offers strategic insights for developing Sumatra’s role in Indonesia’s maritime trade network.

Optimizing Green Vehicle Routing Problem for Halal and Non-Halal Products using Salp Swarm Algorithm

Dana Marsetiya Utama, Aisyah Leilani Salsabilah — Fri, 31 Oct 2025 00:00:00 +0000

Modern distribution systems must clearly distinguish between halal and non-halal items, particularly in areas with sizable Muslim populations and rising awareness of halal integrity. Consumer confidence may suffer, halal principles may be broken, and cross-contamination may result from failing to maintain this separation. This research uses the Green Vehicle Routing Problem (GVRP) approach, which is solved with the Salp Swarm Algorithm (SSA), to develop a joint distribution optimization model for halal and non-halal products in an effort to address these issues. With complete separation and adherence to halal logistics regulations, this methodology aims to reduce Total Distribution Cost (TDC), which comprises fuel expenses, carbon emissions, and operating costs. The SSA method is combined with Large Rank Value (LRV) to convert continuous solutions into practical and feasible route sequences. Simulation results using synthetic data from 20 customer locations show that increasing the population size and SSA iterations consistently reduces the TDC value until stable convergence is achieved. The model also proves to be robust to changes in fuel costs, emissions, and vehicles without altering the route structure. Overall, the results of the research show that the SSA-based GVRP model is capable of providing efficient and sustainable halal logistics solutions. The novelty of this research lies in the explicit integration of halal and non-halal segregation with the SSA-based GVRP optimization framework in a single sustainable distribution system.

Performance Analysis of the IndoBERT–Prophet Hybrid Model for Logistics Applications

Erna Mulyati, Maniah, Noviana, Nia Pardede — Fri, 31 Oct 2025 00:00:00 +0000

The increasing competition in Indonesia’s logistics sector, particularly in digital courier applications, highlights the need for advanced analytical tools capable of understanding and predicting customer sentiment in real time. However, current sentiment analysis methods often lack contextual depth and predictive capability, limiting their practical value for decision-making. This study aims to develop and validate an integrated analytical framework that combines diagnostic and predictive analytics for logistics performance evaluation. The framework integrates a fine-tuned IndoBERT model for sentiment classification and a Prophet model for time-series forecasting, allowing the analysis of user reviews while accounting for external service disruptions. Empirical validation was conducted using 924 user reviews from the PosAja! application by PT Pos Indonesia. The IndoBERT model achieved an impressive 99.5% accuracy, effectively identifying two main complaint categories: application functionality issues and delivery delays. The Prophet forecasting component successfully modeled sentiment trends, revealing spikes in negative sentiment that strongly correlated with technical service disruptions, such as COD feature failures and server maintenance. The results confirm the framework’s robustness in both diagnosing and forecasting sentiment dynamics. User sentiment proved to be a sensitive real-time indicator of service stability and operational performance. The validated IndoBERT–Prophet hybrid framework provides a novel, data-driven approach for proactive decision-making and continuous service improvement in the logistics industry.

Analysis of Antecedent Factors Influencing the Adoption and Conversion of Two-Wheeled Battery Electric Vehicles (BEVs) in East Kalimantan Province

Dimaz Harits, Wahyu Ismail Kurnia, Nugroho Aji Wibowo — Fri, 31 Oct 2025 00:00:00 +0000

The rise in motorcycle ownership in Indonesia has increased energy consumption and greenhouse gas emissions, challenging the country's net-zero target by 2060. To mitigate this, the government is promoting the adoption and conversion of two-wheeled Battery Electric Vehicles (BEVs), but implementation remains below target, implying behavioral factors as a major barrier. This study analyzes the determinants influencing consumer and potential consumer behavior in adopting two-wheeled BEVs in East Kalimantan, a strategic region supporting the Indonesian Capital City. Using the Field Theory framework, the model integrates the Theory of Planned Behavior (TPB), which represents personal factors (Attitude, Subjective Norm, Perceived Behavioral Control, and Intention), and the Electric Vehicle Ecosystem (EVE), which represents environmental factors (Performance, Infrastructure, Price, and Features). Data from 400 respondents were analyzed using SEM-PLS, which explained 65.8% of the variance in adoption intention. The results show that Subjective Norms, Perceived Behavioral Control, Performance, Price, and Features significantly influence intention, while Attitude and Infrastructure do not. These findings reveal that consumers view two-wheeled BEVs primarily as functional alternatives to conventional motorcycles, rather than as environmentally friendly innovations. The contributes of this study is that it extends behavioral research by integrating TPB and EVE into Field Theory, and, practically, it highlights the need for policies that combine economic incentives with behavioral interventions to accelerate BEV adoption in Indonesia.

Cost Model of Activity Oriented Municipal Solid Waste Management: Integration of Activity Based Costing/Management and Causal Loop Diagram

Dedi Dermawan, Agus Mulyadi, Sajidi Wardana — Fri, 31 Oct 2025 00:00:00 +0000

The increasing generation of municipal solid waste (MSW) in Pekanbaru, a densely populated city in Riau Province, has led to higher waste management costs. In 2023, the city generated 1,011 tons of waste daily, with management costs reaching around IDR 93 billion. Traditional cost calculation methods are often inaccurate, failing to account for the activities involved in MSW management. This study develops an activity-based cost management model using Activity-Based Costing/Management (ABC/M) to map costs to specific waste management activities, combined with Causal Loop Diagrams (CLD) to analyze activity relationships and formulate a mathematical cost model. The application of ABC/M identified four primary waste management activities: collection, transportation, processing, and disposal. The results show a total waste management cost of approximately IDR 91 billion, with CLD revealing dynamics such as the impact of incentives on recycling rates and the balancing effects of transportation and waste bank usage on waste generation. This study contributes provides a novel cost model for municipal waste management, offering both theoretical and practical contributions for improving cost efficiency and resource allocation.

Modeling Public Transportation Policy Using Macroscopic Social Media Data Mining

Fri, 31 Oct 2025 00:00:00 +0000

Transportation policies must be created by the government, especially in countries with high population expansion, transportation services are used more to meet daily necessities. Conventional surveys to gauge public opinion are costly and slow; social media offers a macro-level proxy that can complement official data. This study employs large-scale online data mining to build decision support for transportation policy. We collected 19,806 Indonesia-based Twitter posts referencing public transport, private transport, sustainable mobility, and electric vehicles. After preprocessing, we fine-tuned IndoRoBERTa for sentiment classification and applied Latent Dirichlet Allocation for topic modeling. The sentiment model achieved 81.17% accuracy, with precision, recall, and F1-scores all above 0.80. Positive discourse concentrated on private vehicles, public transit, multimodal travel, and environmentally responsible practices, with many users endorsing eco-friendly private cars. Negative discourse emphasized severe air pollution, frequently attributing risk to emissions from private automobiles in Jakarta. Translating these insights into policy, we propose expanding electric-vehicle charging infrastructure, implementing vehicle buy-back/retirement programs, establishing low-emission zones, and promoting biofuels. The results demonstrate that macroscopic social media analytics can surface actionable public preferences and pain points, enabling near-real-time monitoring to inform adaptive and equity-oriented transportation policies. This framework provides a scalable approach for governments in rapidly growing contexts to align service provision with community sentiment while advancing sustainability goals.

Optimization of Socks Production in South African Knitting Plant: A Cost-Effective Alternative to Industry 4.0

Kemlall Ramdass, Isaac Olalere — Fri, 31 Oct 2025 00:00:00 +0000

The textile industry, particularly sock manufacturing, faces increasing demands for productivity and cost efficiency amid global competition. This study presents a comprehensive case study on optimizing sock production in a South African knitting plant as a cost-effective alternative to Industry 4.0 adoption. The Research aims to identify and address key factors contributing to low productivity by employing a data-driven approach integrating Six Sigma methodologies and simulation analysis. Production data revealed that frequent system failures caused significant stoppages, material waste, and reduced operational efficiency, with approximately 8% of production output lost to defective socks. Detailed analysis using Failure Mode and Effect Analysis (FMEA) and a cause–and–effect diagram identified machine- and material-related issues as the primary contributors to poor performance. A planned maintenance strategy was developed based on the Mean Time to Failure (MTTF) of major equipment, and its impact was simulated using Any Logic software. Simulation results demonstrated that implementing scheduled maintenance, reducing failure rates by 50%, could increase system availability to 91% and substantially decrease fabric waste. The novelty of this study lies in demonstrating an effective optimization strategy that avoids the high cost and implementation barriers of full Industry 4.0 integration while achieving comparable productivity gains. This simulation-based maintenance framework provides a practical, data-supported solution for enhancing efficiency, reliability, and competitiveness in conventional manufacturing systems. The findings suggest that similar textile plants can adopt this approach to achieve sustainable production improvements without undergoing complete digital transformation.

Integrating Explainable AI and the Kano Model to Derive Improvement Strategies for Essential Oils from Online Reviews

Akhdan Zaman, Eko Liquiddanu — Fri, 31 Oct 2025 00:00:00 +0000

Growing consumer interest in natural wellness products, particularly essential oils, highlights the need to understand key quality product attributes affecting consumer satisfaction. In the digital era, customer reviews in marketplaces have become the main source of consumer-driven insights for improving production and service processes. However, conventional approaches often fail to systematically extract actionable insights from these unstructured data sources. This study proposes an integrated machine learning framework for three market on essential oils and their derivatives. This framework transforms thousands of online customer reviews into a structured analysis of satisfaction dimensions. The approach uniquely contributes by employing regression model combined with Explainable AI (SHAP) and KANO Classification to systematically applied based on SHAP insights to develop a marketing strategy based on three market segments for essential oil products and their derivatives. Eleven critical satisfaction dimensions were extracted, including aroma, price, packaging, delivery, and others. These segment-specific insights imply that producers should prioritize reliable pricing and delivery for low-tier markets, ensure strict price fairness and value consistency for mid-tier consumers, and, for high-tier segments, focus on integrating diffuser compatibility as a basic requirement while leveraging bonuses as emotional value-adds to enhance customer delight. Theoretically, this research introduces a scalable, Explainable AI-based approach for applying the Kano model to unstructured textual data, overcoming limitations of traditional survey methods. Despite its strengths, this study is limited by the absence of validation for the Kano categorization through survey-based procedures. Future work will address this limitation by conducting perception-based surveys or interviews to validate and refine the inferred categorizations. Nonetheless, this research contributes a methodology and provides actionable strategies for essential oil producers to align product improvements with consumer expectations in digital commerce environments.

Systematic Literature Review of Sustainable Assessment Model in Vocational Higher Education

Suryani, Dadan Umar Daihani, Tiena Gustina Amran, Winnie Septiani — Fri, 31 Oct 2025 00:00:00 +0000

Indonesia prioritizes vocational education to achieve the Golden Indonesia 2045 vision by producing competent, work ready graduates. Despite strategic policies, vocational enrollment remains low relative to academic pathways, and sustainability focused assessment model for vocational higher education are scarce. Therefore, this study aims to map and critically analyze existing sustainability assessment model for vocational higher education using a PRISMA based Systematic Literature Review and bibliometric analysis with VOSviewer. A total of 8,035 records (2018–2024) were retrieved, and the 20 articles that met the inclusion criteria were analyzed for thematic coverage, methodological approach, and integration of sustainability dimensions. The results showed that although many assessment model integrate economic, social, and environmental dimensions partially, few comprehensively addressed work readiness, sustainability literacy, and socio environmental impacts in vocational contexts. Bibliometric mapping further shows a dominance of general higher education studies and an underrepresentation of vocational-specific investigation. This study proposed a contextualized conceptual framework consistent with the Triple Bottom Line (economic, social, environmental) and selected SDG targets characterized by vocational competencies and institutional assessment practices. The framework offers guidance for policymakers and vocational institutions to design assessment systems that improve graduate relevance and institutional sustainability. The study contributes a systematic scientific map and a foundation for empirical testing of the proposed model.

Why Riders Break the Rules: A Structural Equation Modeling Approach to Traffic Violations in a Developing Region

Desrina Yusi Irawati, Nyoman Sri Widari, Armadeo Ruben Canariesa — Fri, 31 Oct 2025 00:00:00 +0000

Traffic violations remain a major contributor to road traffic accidents in Indonesia. Despite government initiatives, limited research has examined the psychological and contextual factors driving this behavior. This study extends the Theory of Planned Behavior (TPB) by incorporating risk perception, habit, emotional condition, environmental condition, and legal knowledge and awareness. A structured questionnaire (N=100) was administered to motorcyclists and/or car drivers in East Java; items were derived from established scales and refined using field observations and a pilot test. Respondents were selected using stratified area sampling to ensure relevance. Data were analyzed using PLS-SEM (SmartPLS). Key findings: attitude and perceived behavioral control significantly predicted behavioral intention; intention strongly predicted actual violation behavior; risk perception negatively predicted permissive attitudes. Habit, subjective norms, emotional and environmental conditions, and legal knowledge were not significant predictors. The study contributes theoretically by refining TPB with risk perception as an antecedent of attitude, and practically by suggesting interventions targeting attitudes and risk awareness supported by technology-assisted enforcement in developing-country contexts.