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Jurnal Optimasi Sistem Industri

JOSI
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Published by Universitas Andalas

ISSN : 20884842 EISSN : 24428795 DOI : -

Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Jurnal Optimasi Sistem Industri (JOSI) is a peer-reviewed journal that is published periodically (April and October) by the Department of Industrial Engineering, Faculty of Engineering, Universitas Andalas, Padang.

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Articles 8 Documents

Search results for , issue "Vol. 23 No. 2 (2024): Published in January 2025" : 8 Documents clear

Unveiling the Landscape of Sustainable Logistics Service Quality: A Bibliometric Analysis Abdelaziz, Shereen; Munawaroh, Munjiati
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

In today's environmentally conscious world, where environmental sustainability and consumer demand for responsible business practices are Sustainable Logistics Service Quality (SLSQ) has emerged as a critical focus in supply chain management, driven by increasing environmental concerns and consumer demand for responsible business practices. This study conducts a bibliometric analysis of 546 Scopus-indexed documents published between 1994 and 2024, systematically uncovering key research trends, thematic clusters, and gaps in SLSQ. Findings reveal a marked increase in SLSQ research since 2013, spurred by regulatory pressures, advancements in digital technologies, and growing consumer expectations for sustainable logistics. Dominant themes include the integration of cutting-edge technologies such as artiﬁcial intelligence (AI), big data analytics, blockchain, and sustainable transportation methods, which collectively enhance logistics service quality while reducing environmental impacts. Additionally, a notable trend is the alignment of logistics services with sustainability goals, reﬂecting both academic interest and industry imperatives to lower carbon footprints and improve resource eﬃciency, particularly in sectors like e-commerce. Despite these advancements, the study identiﬁes signiﬁcant gaps, particularly the lack of multidimensional metrics capable of comprehensively evaluating SLSQ across social, environmental, and economic dimensions. This highlights an urgent need for standardized and holistic frameworks to guide logistics providers in achieving operational eﬃciency and sustainability objectives. By bridging service quality and sustainability, this research addresses an underexplored area and provides a foundation for future scholarly work in SLSQ. Practical implications include guiding logistics providers and policymakers in formulating sustainable practices that align with regulatory requirements and enhance customer satisfaction. For academia, it oﬀers a pathway to develop robust SLSQ metrics and frameworks, advancing sustainable logistics strategies and fostering a more eﬃcient, eco-friendly, and customer-centric logistics ecosystem.

Optimizing Demand Forecasting Method with Support Vector Regression for Improved Inventory Planning Palgunadi, Tryantomo Lokhilmahful; Fitriana, Rina; Habyba, Anik Nur; Liang, Yun-Chia
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Problems arising from suboptimal production planning can cause inventory management to be less effective and efficient in the company. The lack of integrated presentation of information also causes less efficiency in making decisions. This study aims to obtain the best kernel function forecasting model by predicting ground rod sales using the Support Vector Regression (SVR) method in order to determine the level of forecasting accuracy and the results of ground rod forecasting in the future which are presented in an optimal data visualization. This problem-solving is done with the Support Vector Regression method, which consists of linear kernel functions, polynomial kernel functions, and radial basis function (RBF) kernel functions with the Grid Search Algorithm. Based on the results of the best parameter search that has been done using the grid search algorithm, it can be concluded that the best kernel function forecasting model is a linear kernel function with a value of C = 100 and ε = 10-3. The accuracy of this forecasting model has a MAPE value of training data and testing data of 2.048% and 1.569%, where this value is the smallest MAPE value compared to the MAPE value of the other two functions. After getting the best model, forecasting was carried out within five months, obtaining an average of 6,647 monthly pieces. The results of forecasting and historical sales are reviewed in a visualization of Business Intelligence data so that it is well exposed, where the forecasting shows an increase from every month.

Optimizing the Supply Chain for Recycling Electric Vehicle NMC Batteries Kasy, Fransisca Indraningsih; Hisjam, Muhammad; Jauhari, Wakhid Ahmad; Syed Hassan, Syed Ahmad Helmi
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

The rapid growth of electric vehicle production has led to increased waste batteries that can no longer be used. This increase causes environmental and economic challenges. Lithium-ion battery waste harms the environment as it contains toxic and ﬂammable chemicals. New raw materials need to be procured economically due to the need for more infrastructure and a circular economy. Therefore, the solution to overcome the impact of the accumulation of lithium battery waste is to recycle the battery. Recycling end-of-life batteries is necessary to mitigate material supply risks, reduce demand for new materials, and mitigate harmful environmental and health impacts. This study aims to provide a conceptual model for the supply chain network design of electric vehicles' Nickel Manganese Cobalt (NMC) battery recycling process. We developed a mathematical model to determine the allocation of multi-product recycling products from multi-suppliers and other related entities such as manufacturers and landﬁlls over multiple periods. The analysis method utilizes techno-economic investment feasibility analysis and load distance method. The problem in the recycling process supply chain network is formulated in a Mixed Integer Linear Programming (MILP) model. The MILP optimization results show that the proposed model produces a globally optimal solution for allocating NMC batteries. The application of this study is to provide a solution to the treatment of waste batteries from electric vehicle end-users in Java Island, Indonesia. In addition, it can develop economic opportunities in the waste battery recycling business in the electric vehicle industry. It is building a contribution to a sustainable electric vehicle battery management system by reducing the dependence on demand for new materials from mining and analyzing the sustainability of the NMC electric vehicle battery recycling process.

Enhanced Sustainability Assessment Framework for Plywood Manufacturing: A Multi-Method Approach Using Delphi Technique, BWM, and S-VSM Garside, Annisa Kesy; Rosiani, Tyas Yuli; Amanda, Adelya; Saputro, Thomy Eko; e Oliveira, Eduardo
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Sustainable manufacturing has emerged as a critical priority in addressing the complex environmental, social, and economic challenges of modern industry. This study focuses on the plywood sector, a signiﬁcant contributor to manufacturing, which faces distinct sustainability issues such as high energy consumption, material ineﬃciencies, and hazardous working conditions. To address these challenges, the research introduces workload and noise level as critical indicators for assessing sustainability, broadening the scope of traditional evaluation methods. A multi-method framework was employed, integrating the Delphi technique to identify key sustainability indicators, the Best Worst Method (BWM) to assign weights to these indicators, and Sustainable Value Stream Mapping (S-VSM) paired with a Traﬃc Light System (TLS) to evaluate and visualize the Manufacturing Sustainability Score (MSS). Applied to a plywood manufacturing case study, the framework highlighted areas requiring improvement, particularly in worker well-being and operational safety, while demonstrating the industry's moderate overall eﬃciency. By oﬀering actionable insights for improving resource use, operational processes, and employee conditions, this framework provides a practical tool for industry managers aiming to enhance sustainability. Furthermore, its adaptability makes it a valuable reference for other manufacturing sectors seeking to implement resource-eﬃcient and sustainable practices. This research not only ﬁlls critical gaps in sustainability assessment but also contributes to advancing industry practices by emphasizing holistic and innovative approaches to manufacturing eﬃciency.

Developing an Industry-Specific Lean 4.0 Readiness Assessment Tool: A Case for the Chemical Sector Sulistyo, Arif Budi; Karningsih, Putu Dana; Alvandi, Samira
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

In an era where digital transformation is increasingly imperative, many industries struggle to navigate the complexities of technological adoption and operational efficiency. Lean principles, which emphasize waste reduction and process optimization, provide a robust foundation for digital transformation, particularly in the chemical industry, where unique operational challenges exist. This research aims to develop an integrated Lean 4.0 readiness assessment tool to bridge the gap between leanness and Industry 4.0 readiness. The study begins with a literature review on existing lean and Industry 4.0 readiness measurement tools and integrates them to create a new framework, using the Indonesia Industry 4.0 Readiness Index (INDI 4.0) as a reference, tailored specifically to the chemical industry. Expert interviews are conducted to refine the assessment tool, ensuring alignment with real-world industry conditions and practical insights. A Delphi-based expert consensus method combined with a fuzzy approach for handling imprecision in indicator ratings is employed to validate the framework, resulting in five key dimensions and 86 indicators. By gathering expert input, the tool addresses the chemical industry’s specific challenges and simplifies readiness evaluation, helping companies assess their preparedness for digital transformation and identify areas for improvement. The resulting framework enables chemical companies to bridge readiness gaps and prioritize targeted enhancements. Furthermore, this tool has the potential to serve as a scalable model for other industries, fostering more efficient and strategic digital transformation aligned with Industry 4.0 objectives globally.

A Solution Approach on Reducing Defects in Batik Tanah Liek Production Process of a Small and Medium-sized Enterprise Sutanto, Agus; Putri, Nilda Tri; Alqifti, Tessa; Yusof, Sha'ri Mohd
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Small and medium enterprises (SMEs) often struggle with implementing eﬀective quality management practices, especially in traditional industries like batik production. These challenges include ensuring consistent product quality to diﬀerentiate from competitors and attract customers. This study focuses on addressing quality control issues in small-scale Batik Tanah Liek production, where signiﬁcant defects persist. The research aims to assess existing practices, identify defect causes, and propose solutions to enhance product quality and reduce rejection rates. These eﬀorts contribute to improving production eﬃciency and supporting the sustainability of this traditional craft. The study employs a systematic approach combining quality management methodologies, including data collection, problem identiﬁcation, brainstorming, the Failure Mode and Eﬀects Analysis (FMEA) approach, and actionable recommendations. Data was gathered through a questionnaire to capture perspectives on defects and quality control issues in batik production. Key quality challenges identiﬁed include faded batik, torn fabric, and incorrect motifs. Analysis revealed that the primary cause of incorrect motifs is the malfunctioning canting tool, which hinders proper wax application. Additionally, defects in dyeing and boiling processes contribute to fabric fading and tearing, exacerbating quality issues. The ﬁndings underscore the need for systematic solutions, such as creating clear work instructions, designing Standard Operating Procedures (SOPs) for process consistency, and implementing preventive maintenance schedules for equipment. By addressing these issues, the study provides practical interventions to improve production quality. These measures not only enhance the economic viability of SMEs but also play a crucial role in preserving the cultural heritage of Batik Tanah Liek. The implications of this research highlight the potential for broader adoption of quality management practices in traditional industries to ensure their sustainability in competitive markets.

A Fuzzy Multi-Criteria Approach for Selecting Open-Source ERP Systems in SMEs Using Fuzzy AHP and TOPSIS Utama, Dana Marsetiya; Ibrahim, Muhammad Faisal; Jabari, Ahmed Nedal Abid Al Kareem
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v23.n2.p167-187.2024

In a rapidly growing and competitive business era, selecting an open-source Enterprise Resource Planning (ERP) system is a critical step to support the eﬃciency and eﬀectiveness of company operations. This research aims to propose an innovative methodology by integrating the fuzzy Analytical Hierarchy Process (fuzzy AHP) and fuzzy Technique for Order Preference by Similarity to the Ideal Solution (fuzzy TOPSIS) to improve the open-source ERP selection process. The method involves eight criteria and 26 sub-criteria to comprehensively evaluate 11 open-source ERP alternatives, speciﬁcally for SMEs in the transportation services sector in Indonesia. System quality has been identiﬁed as a critical factor in the selection of an open-source ERP system, with particular emphasis on aspects such as security and reliability. These sub-criteria are considered the most inﬂuential in determining the suitability of a system. The analysis further indicates that the 10th ERP alternative as the best choice, consistently outperforming others in meeting the deﬁned criteria. Additionally, sensitivity analysis conﬁrmed the robustness of this choice, demonstrating its stability and eﬀectiveness despite changes in criteria weights. Beyond its practical implications for SMEs, this research contributes a versatile evaluation framework that can be adapted to other industries seeking eﬀective ERP solutions. The ﬁndings emphasize the importance of structured decision-making in technology adoption, oﬀering comprehensive and reliable guidance for organizations aiming to optimize their operations through open-source ERP systems. This study not only bridges a critical gap in ERP selection for SMEs but also establishes a methodological foundation for future research and applications across diverse industry sectors.

Towards Safer Workplace: A Survey-Based Study on Developing a Safety Climate Model for the Indonesian Paper Industry Rahdiana, Nana; Suhardi, Bambang; Damayanti, Retno Wulan; Susanto , Novie; Rohani, Jafri Mohd
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v23.n2.p130-148.2024

A reliable safety climate model is essential for evaluating safety behavior and predicting risks such as accidents or injuries, yet no research has speciﬁcally addressed the safety climate in the paper industry, either globally or in Indonesia. Recognized as high-risk due to its reliance on large machinery and hazardous chemicals, the paper industry has been understudied in this context. This research addresses the gap by developing a safety climate model tailored to the Indonesian paper industry, following a rigorous methodology that included a literature review, model design, validation processes, and Goodness-of-Fit testing. The study identiﬁed nine dimensions and 36 initial indicators, with strong content validity conﬁrmed through Aiken’s V index, and reﬁned through a survey of 313 employees—including managers, supervisors, and operators—at a paper factory in West Java, Indonesia. Conﬁrmatory factor analysis (CFA) led to the ﬁnal model, comprising nine dimensions and 32 validated indicators, achieving excellent ﬁt across key criteria. These dimensions include management commitment, safety environment, safety communication, safety involvement, safety rules and procedures, safety training, safety competence, work pressure, and local wisdom. The validated model oﬀers valuable insights into safety practices, providing a practical framework for improving safety performance in the Indonesian paper industry. By fostering a proactive safety culture and addressing sector-speciﬁc risks, this model has the potential to signiﬁcantly reduce workplace accidents and improve overall safety performance, marking an important advancement in industry-speciﬁc safety research.

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Home Page

OAI Link

Editorial Team

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Contact Name Rika Ampuh Hadiguna

Contact Email hadiguna@ft.unand.ac.id

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Journal Mail Official hadiguna@ft.unand.ac.id

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Location Kota padang, Sumatera barat INDONESIA

Abstract

Abstract

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Abstract

Abstract

Contact Name
Rika Ampuh Hadiguna

Contact Email
hadiguna@ft.unand.ac.id

Phone
-

Journal Mail Official
hadiguna@ft.unand.ac.id

Editorial Address
-

Location
Kota padang,

Sumatera barat

INDONESIA