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Spektrum Industri
Published by Universitas Ahmad Dahlan
ISSN : 16936590     EISSN : 24422630     DOI : https://doi.org/10.12928/si.vxix.xxx
Core Subject : Science, Social, Engineering,
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Spektrum Industri ISSN 1693-6590(print); ISSN 2442-2630(online) is a Journal that publish scientific articles in the science scope related to engineering and/or industrial management both research and theoretical. Literature review will be considered if it is written by an expert.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 90 Documents
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Effects of Physical Work Environment Factors on Task Duration and Error in Manual Banking Transactions Nachnul Ansori; Silvia Nur Lathiifa; Ernaning Widiaswanti; Issa Dyah Utami
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.657

Abstract

The manual cash handling tasks require consistent attention and precision and can be affected by the physical working conditions. The aim of this study is to examine the effects of lighting, temperature, and aroma on the task completion time and the counting errors in simulated banking teller activities. In a laboratory experiment, six participants (three males and three females) aged between 20 and 24 years were selected based on their similar money-counting skills. We used a completely randomized factorial design with 2 × 2 × 2 factors with two lighting levels (150 and 350 lux), two temperatures (24 and 26 °C) and two aromas (lemongrass and rosemary). Performance measures were time to complete the task and number of counting errors. Statistical tests including analysis of variance (ANOVA) followed by Tukey's post hoc test where applicable were used to analyze the data. The results showed that lighting and aroma had a significant impact on the task performance, especially in female participants, and temperature had a significant impact on the task completion time in male participants. Within the experimental settings, the optimal condition was identified as the combination of 150 lux, 24°C, and the lemongrass aroma. These results suggest that physical workplace conditions may influence the speed and accuracy of simulated cash-handling tasks, with possible differences in response between male and female participants. This research provides preliminary experimental evidence to consider environmental factors in the ergonomic design of workplaces for manual banking activities.
From Static Risk Lists to Dynamic Risk Behavior: An Integrated Mixed-Method and Causal Loop Modeling Approach for Operational Risk in Indonesian EPC Firms Drajat Indrajaya; Parwadi Moengin; Dadang Surjasa; Sally Cahyati; Etanto Heiliano Wijayanto
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.670

Abstract

Operational risks in Engineering, Procurement, and Construction (EPC) firms are interconnected and may evolve through interactions among organizational, project, and external factors. However, conventional risk assessment approaches often emphasize risk identification and prioritization without explicitly representing potential feedback relationships among risk factors. This study develops a qualitative causal framework for operational risk in Indonesian EPC firms by integrating expert-based risk-dimension validation with systems thinking and Causal Loop Diagram (CLD) modelling. The study employed a sequential two-stage approach. First, a structured literature synthesis identified 15 operational risk dimensions, which were operationalized into 45 measurement items and assessed by seven EPC experts using Content Validity Ratio (CVR), Content Validity Index (CVI), and Relative Importance Index (RII). Five core dimensions were retained: Strategic & Business Risk, Human Resource Risk, Customer & Stakeholder Risk, Environmental & Sustainability Risk, and Reputational Risk. Second, the validated dimensions were incorporated into an influence diagram and subsequently developed into a CLD. Causal directions and polarities were established through conceptual definitions, EPC operational knowledge, risk-management principles, and expert-based structural verification rather than inferred from CVR, CVI, or RII results. The resulting CLD identifies one potential reinforcing mechanism associated with risk escalation and two potential balancing mechanisms associated with governance-based and reputation-driven corrective responses. The study contributes an expert-verified qualitative causal architecture that extends operational risk assessment from variable identification toward a systems-based representation of potential feedback mechanisms. Historical pattern assessment showed directional consistency for 13 of 14 loop-specific causal relationship instances, with R1 partially supported and B1 and B2 showing consistent historical patterns.
Analyzing Bounded Hub-Spoke Allocation in Single Allocation Hub Location Problem Fran Setiawan
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.676

Abstract

The hub location problem (HLP) is widely used to design hub-and-spoke networks by consolidating flows through selected hub facilities. However, standard formulations may produce solutions in which some hubs are connected to very few spokes, while others serve a disproportionately large number of spokes, resulting in inefficient hub utilization. This study aims to investigate the impact of imposing explicit lower bound and combined lower and upper bounds on hub–spoke allocations to improve hub utilization. The contribution of this study is to introduce two bounded spoke allocation constraints and systematically evaluating their impact on computational performance, total cost, network structure, and hub location decisions. A flow-based single allocation hub location formulation is adopted, and computational experiments are conducted on the CAB and TN benchmark datasets under various parameter settings. The results show that the lower bound eliminates hubs with very few spokes, while the upper bound limits excessive concentration of spokes, leading to more controlled hub and spoke configurations. The proposed constraints may also alter hub location decisions. The impact on total cost is small, with average increases of about 1.23% and 0.99% for the lower bound model, and 1.38% and 1.52% for the combined lower and upper bounds model in the CAB and TN datasets, respectively. Although computational effort increases for larger instances, the proposed approach provides decision-makers with a practical mechanism for controlling hub utilization.
A Hybrid Stochastic Optimization and Simulation Approach for Multi-Stage Production–Procurement Planning under Uncertainty Paulina Kus Ariningsih; Carles Sitompul; Titi Iswari; Giovano Alberto
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.679

Abstract

Multi-stage manufacturing firms that source raw materials through both long-lead-time import contracts and volatile spot markets must coordinate procurement and production under supply and demand uncertainty. Managing these decisions separately leads to excessive reliance on spot markets, unstable inventories, and unbuffered downside cost risk. This study aims to develop a novel integrated stochastic optimization framework that jointly plans procurement and multi-stage production for a real-world textile supply chain. The framework's novelty lies in embedding a Conditional Value-at-Risk (CVaR) measure directly into a multi-stage stochastic input–output production–procurement model, so that sourcing-channel selection and production scheduling are optimized jointly rather than sequentially. The approach combines a risk-aware CVaR procurement model with a stochastic input–output production scheduling model that captures material flow across processing stages. The two are accompanied by a Monte Carlo scenario-generation architecture that represents demand and spot-price uncertainty. System performance is evaluated across 100 stochastic scenarios over a 52-week horizon, using a dataset calibrated from an industrial textile system. Results show the framework maintains a 100% service level (zero expected backlog) across all scenarios. As the initial-inventory target rises from 1× to 2× the target Days of Inventory on Hand (DOH), total operational cost increases from about USD 2.15 million to USD 2.80 million (a 30% rise), while the 0.95-level CVaR increases from about USD 1.66 million to USD 2.17 million. This reveals an explicit, quantifiable trade-off between inventory buffering and downside cost risk. The model also shifts sourcing away from expensive spot purchasing as buffering increases. This study contributes to developing a framework that offers a practical, risk-aware decision-support tool for firms balancing import contracts against spot volatility, and demonstrates the value of synchronizing procurement and production rather than planning them in isolation.
Optimizing LPG Distribution Resilience: A Fuzzy-Heuristic Approach and Monte Carlo Simulation for Single-Manifold Bottleneck Mitigation in Refinery Facilities Diaz Mondrian; Eko Liquiddanu
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.686

Abstract

Operational bottlenecks in LPG refinery distribution can arise from single-manifold constraints, creating a critical trade-off between throughput maximization and product quality assurance. Existing scheduling approaches often address vessel evacuation and blending separately, leaving a gap in integrated decision models that simultaneously consider infrastructure constraints, production fluctuations, and quality specifications. This study aims to develops an integrated simheuristic decision-support framework combining a five-tier Lexicographic Heuristic Priority Rule, Fuzzy Logic membership functions, and a Zero-Sealing mechanism to prevent off-specification products from entering distribution. The framework enables refinery managers to determine achievable throughput through a single manifold while maintaining product quality. A discrete-event simulation with hourly time steps was developed over a 31-day operational horizon using historical vessel arrival, distribution, and production data from a refinery case. Model performance was evaluated through Monte Carlo simulation under four uncertainty dimensions: maritime arrival variability, batch-size variation, pipeline degradation, and upstream feed-quality fluctuations. Sensitivity analysis was conducted to identify critical operational thresholds. Across the tested scenarios, the framework recorded no overfill incidents or quality specification violations and achieved a mean domestic gas supply of approximately 1,355 MT/day, evacuating nearly all available upstream production. Pipeline rate degradation was identified as the most sensitive parameter, affecting both throughput evacuation and quality control when capacity declined below a critical level. The findings demonstrate that evacuation capacity and quality management are structurally interdependent in single-manifold systems. The proposed framework contributes provides a quantitative decision-support tool for reducing off-specification risks and informing refinery infrastructure investment decisions.
Development of a Quality Control Framework for Leather Craft MSME Products in Yogyakarta using Integrated BWM-FMEA-GRA Umi Reza Lestari; Nafis Khuriyati; Anggoro Cahyo Sukartiko
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.694

Abstract

Leather craft MSMEs have substantial economic potential but often struggle to maintain consistent product quality because production relies on manual craft, artisan experience, and limited formal process controls.  At the leather craft MSME specializing in leather bags examined in this study, product defects and customer complaints led to rework, material waste, and potential reputational loss. This study develops a case-based quality failure risk prioritization framework that integrates the Best-Worst Method (BWM), Failure Mode and Effects Analysis (FMEA), and Grey Relational Analysis (GRA). Although FMEA, BWM, and GRA have each been applied separately in prior quality-risk studies, their integration remains limited in the leather craft MSME context. Failure risks were identified through observation and interviews, weighted by severity, occurrence, and detection using BWM, rated using FMEA, and prioritized using GRA. The analysis identified 35 failure risks across 13 production stages. Detection received the highest criterion weight, followed by severity and occurrence. GRA ranked 12 highest-priority risks across nine stages, led by inappropriate pattern-making and peeled or scratched product components. For the priority failure risk occurring at the raw material stage, moldy leather was further examined in accordance with SNI 06-0335-1989 (Indonesian National Standard for Cow Leather for Bags and Suitcases – Quality Requirements and Test Methods). The test results revealed nonconformity in moisture content, total ash content, and thickness. These findings indicate that the integrated BWM-FMEA-GRA framework provides a systematic basis for prioritizing quality failure risks and formulating targeted, appropriate quality control recommendations that address the resource constraints of leather craft MSMEs.
The Effect of Noise on Learning Achievement through Students Cognitive Functions: A Stroop Test-Based Mediation Analysis Marulan Andivas; Alex Kisanjani; Nana Sugiono; Joshua Primadani; Ari Andriyas Puji
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.721

Abstract

Environmental noise exposure in schools near airports may negatively impact students’ cognitive functioning and academic performance. However, the cognitive mechanisms underlying the relation between noise exposure and learning achievement are still poorly understood. This study aims to explore the direct and indirect associations of environmental noise exposure with learning achievement, with a mediating variable of cognitive function measured by the Stroop Test. This research was done on 120 students of elementary, junior high and vocational high school who lived in the vicinity of Sultan Aji Muhammad Sulaiman Sepinggan Airport, Balikpapan, Indonesia. The data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) with 10.000 bootstrap resamples. The results indicated that environmental noise exposure was negatively associated with cognitive function (beta = -0.981, p < 0.001), and cognitive function was positively associated with learning achievement (beta = 2.309, p < 0.001). There was a significant and positive direct relationship between noise exposure and learning achievement (beta = 1.470, p < 0.001), and a significant and negative indirect relationship through cognitive function (beta = -2.266, p < 0.001, 95% CI [-2.729, -1.852]). Overall, the effect was negative and significant (beta = -0.796, p < 0.001) suggesting competitive mediation. These findings indicate that cognitive function is an important mediating factor between environmental noise exposure and learning achievement. Our results provide empirical support for a cognitive pathway based on Stroop interference linking airport-related environmental noise and learning outcomes and provide insights for the assessment of environmental conditions and support of cognitive performance in educational contexts.
A Trend-Driven Framework for Integrated SKU-to-Pod Assignment and Replenishment Policy in Robotic Mobile Fulfillment Systems (RMFS) Salsabila Herwening Mileniadewi; Shuo-Yan Chou; Sinta Rahmawidya Sulistyo; Anna Maria Sri Asih
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.722

Abstract

Robotic Mobile Fulfillment System (RMFS) performance is greatly affected by stock-keeping unit (SKU) assignment and replenishment decisions, especially with the changing e-commerce demand. However, current studies typically treat these decisions in isolation, without paying adequate attention to changing demand patterns. The aim of this study is to develop and evaluate a trend-driven framework that combines demand-based SKU clustering, SKU-to-pod assignment and dynamic replenishment strategies for improving the operational performance of RMFS. The proposed framework uses machine-learning based clustering to group SKUs according to their demand characteristics, and then implements capacity-constrained pod assignment and replenishment policies for each cluster. An agent-based simulation was conducted with ten replications to test the proposed strategy against a static baseline, employing order throughput, replenishment-to-picking ratio, and pod utilization as performance indicators. The results show that the proposed framework significantly increases the order throughput from 74.75% to 93.44% (an increase of 18.69 percentage points) and significantly decreases the replenishment-to-picking ratio from 38.98% to 34.56% (a decrease of 4.42 percentage points). Pod utilization remains unchanged, meanwhile. These results suggest that the combination of demand-driven assignment and adaptive replenishment can improve fulfillment efficiency while maintaining pod utilization. This paper proposes an integrated simulation-based decision-support framework for demand clustering, pod assignment and replenishment decisions to enable adaptive RMFS operations under volatile e-commerce demand.
Mapping the End-of-Life Electric Motorcycle Battery System in Indonesia: A Multi-Actor Causal Loop Diagram of OEM, Informal, User, and Government Interactions Annie Purwani; Siti Mahsanah Budijati; Aufha Rafhika; Salsabiela Nurul Alisyah; Meisya Putri Wardani
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.741

Abstract

Indonesia’s rapid electric-motorcycle adoption requires circular end-of-life (EoL) battery management to retain material value and reduce environmental risk. In Yogyakarta, unclear return and processing arrangements risk diverting used batteries into informal channels that are economically attractive but often unsafe and poorly traceable. This study develops a stakeholder-informed Causal Loop Diagram (CLD) to map circular pathways for EoL batteries across OEMs, informal workshops, users, and government, and to support a circular battery supply-chain framework. The model integrates market growth, information, service access, incentives, OEM take-back responsibility, informal repair and reuse, and regulation within a single systems perspective. Variables were identified through literature and policy review, refined with AI-assisted reference exploration, and validated through a survey of 98 users, interviews with 8 dealer/OEM representatives and 4 informal actors, and a focus group discussion (FGD) that assessed variable relevance, causal relationships, polarity, and overall CLD structure. The final model comprises 67 variables, 14 reinforcing loops, and 5 balancing loops. It shows that reduced-performance batteries may enter repair, refurbishment, reuse, storage, transfer, or final treatment pathways. Reinforcing dynamics arise from market expansion, informal economic benefits, and convenience, whereas formal incentives, regulation, and risk mitigation generate balancing effects that can redirect flows toward higher-value circular pathways. Key leverage points include accessible formal collection, operational OEM take-back with diagnostic and downstream capacity, and trained informal workshops linked to traceable handover. As a structural model, the CLD does not quantify parameters or simulate outcomes, but provides a basis for future system-dynamics modelling of material recovery, environmental risk, and circular value creation in electric-motorcycle battery supply chains.  
Manufacturing and Performance Evaluation of Ecoflex-Based Flexible Strain Sensors Reinforced with MWCNTs and Recycled Battery Carbon Muhammad Luthfi Hakim; Ari Iswanto; Sigit Yatmono; Afri Yudantoko; Mohamad Shaiful Abdul Karim; Didik Hariyanto
Spektrum Industri Vol. 24 No. 2 (2026): Spektrum Industri - October 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v24i2.742

Abstract

Flexible strain sensors hold great potential for applications in wearable electronic devices, human motion monitoring, and rehabilitation systems. However, the development of such sensors still faces challenges in producing conductive networks that are both sensitive and stable while reducing reliance on commercial conductive materials. This study developed an Ecoflex/MWCNT–RBC-based flexible strain sensor (FSS) by utilizing recycled battery carbon (RBC) obtained from carbon rods in zinc–carbon battery waste. The RBC was separated, washed, dried, crushed, and sieved into a powder, then mixed with multi-walled carbon nanotubes (MWCNT) in isopropyl alcohol using ultrasonic homogenization. The mixture was applied to a pre-cured Ecoflex layer, fitted with copper electrodes, and encapsulated using an Ecoflex layer to produce a layered sensor structure. The morphology and conductive network of the sensor were analyzed using SEM, while its electromechanical performance was evaluated through testing of sensitivity, linearity, cyclic response, response and recovery times, and durability. The sensor produced a measurement factor of 15.42 over a strain range of 0–100%, with a linearity (R²) of 0.994. Response and recovery times were recorded at 70 ms and 70 ms, respectively, while the sensor’s stability was maintained for up to 500 load–unload cycles at 80% strain. These results demonstrate that RBC can serve as a secondary conductive material alongside MWCNT in producing flexible, responsive, and stable strain sensors. This approach offers a sustainable strategy for converting carbon from battery waste into value-added functional materials for wearable sensor applications.

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