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INDONESIA
Journal Industrial Servicess
Published by Universitas Sultan Ageng Tirtayasa
ISSN : 24610623     EISSN : 24610631     DOI : -
Core Subject : Economy, Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation
Jurnal Industrial Servicess merupakan wadah bagi peneliti untuk publikasi jurnal hasil penelitian yang ruang lingkupnya melingkupi: Logistics & Supply Chain Management Operations Research Quality, Reliability, and Maintenance Management Data Mining & Artificial Intelligence Production Planning & Inventory Control Ergonomics & Human Factors Information Systems & Technology Service Management Sustainability Human Resources Economic
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 13 Documents
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Search results for , issue "Vol 12, No 1 (2026): April 2026" : 13 Documents clear
Scenario-based discrete-event simulation for production bottleneck identification and capacity optimization in garment small and medium enterprises Purnama, Dwi Adi; Haryanto, Zelania In
Journal Industrial Servicess Vol 12, No 1 (2026): April 2026
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jiss.v12i1.35532

Abstract

This study addresses production system inefficiencies in garment manufacturing, particularly related to flow imbalance, bottlenecks, and low throughput in multi-stage production lines. A discrete-event simulation (DES) model was developed using FlexSim 6.0 to evaluate material handling and processing performance in a six-stage garment production system. The model was validated using statistical tests, confirming its ability to represent real-world system behavior. The results indicate that severe capacity imbalance at the sewing stage leads to critical system inefficiencies, characterized by extremely high blocking rates (up to 92.10%), high resource idleness in upstream processes, and low throughput performance, with only 60 units produced from 760 input materials. To address this issue, multiple improvement scenarios were evaluated through simulation-based experimentation. The findings show that increasing capacity at key bottleneck stages significantly improves system performance, with the best scenario increasing daily output to 171–184 units. Statistical analysis confirms that the improvements are significant across all scenarios. This study contributes methodologically by demonstrating a simulation-based framework for identifying bottlenecks, evaluating system performance, and testing capacity improvement strategies in garment production systems. Unlike case-specific problem-solving approaches, the proposed framework provides a generalized analytical approach applicable to similar multi-stage manufacturing environments. The findings highlight the importance of capacity balancing and system-level optimization in improving production efficiency. The proposed approach offers practical insights for production system design and supports the application of simulation as a decision-support tool in industrial engineering contexts.
GIS-based hybrid AHP–random forest model for optimal waste transfer station siting: A case study Syahputra, Rizki Agam; Sofiyanurriyanti, Sofiyanurriyanti; Kasmawati, Kasmawati; Irawan, Risnadi; Kamal, Mustafa; Agustavia, Putri Sarina
Journal Industrial Servicess Vol 12, No 1 (2026): April 2026
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jiss.v12i1.34731

Abstract

Rapid urbanization and post-disaster recovery in developing cities present significant challenges for municipal solid waste management, escalating operational costs and environmental burdens. The primary logistical bottleneck is often the inefficient placement of intermediate waste infrastructure. This study addresses this gap by proposing and validating a novel hybrid spatial decision support framework for the optimal siting of Temporary Waste Transfer Stations (TWTS) in Meulaboh, Indonesia. The framework integrates a Geographic Information System (GIS) with the Analytic Hierarchy Process (AHP) and a Random Forest (RF) machine learning model. AHP structures the problem using expert knowledge and local regulatory standards to generate an initial suitability map. To overcome AHP's linearity and subjectivity, this map generates pseudo-labeled data to train the RF model, which learns complex, non-linear relationships among spatial factors. The RF model demonstrated exceptional performance with an Area Under the Curve (AUC) of 0.96. The framework evaluated 43 villages (Gampong), identifying specific areas in Meureubo and Johan Pahlawan as top candidates due to favorable land use and proximity to road networks. This hybrid approach offers a robust, transparent, and scalable methodology for post-disaster urban infrastructure planning.
Developing a readiness instrument for LPG-to-induction stove transition: A Technoware, Humanware, Infoware, and Orgaware (THIO) approach Anshori, Hasna Wahidaturrasyidah; Damayanti, Retno Wulan; Pujiyanto, Eko
Journal Industrial Servicess Vol 12, No 1 (2026): April 2026
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jiss.v12i1.38518

Abstract

The transition to induction stoves is a strategic effort to support decarbonization and electrification goals. The success of this transition depends not only on policy and infrastructure, but also on technical, social, informational, and institutional readiness. This study aims to develop and validate a readiness assessment instrument based on the Technoware, Humanware, Infoware, and Orgaware (THIO) framework to evaluate the readiness of stakeholders — including household users and institutional actors — in the transition process. A sequential qualitative–quantitative approach was applied, involving a systematic literature review and expert validation to ensure content validity, followed by empirical testing through a survey of 260 respondents. Data were analyzed using Confirmatory Factor Analysis (CFA). The results show that all indicators across the four THIO dimensions are valid and reliable, with factor loadings, composite reliability, and average variance extracted all exceeding the recommended thresholds. The measurement model also achieved a good overall fit. The validated instrument provides a robust and multidimensional tool for assessing readiness for the transition to induction stoves. Practically, it can be immediately utilized by government agencies, energy institutions, and related stakeholders as a diagnostic tool to systematically identify readiness gaps across technical, human, informational, and organizational dimensions, thereby supporting evidence-based prioritization and phased planning of energy transition programs. Overall, this study contributes to strengthening readiness measurement approaches for clean and sustainable energy transitions.

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