Pub Date : 2023-12-18DOI: 10.25077/josi.v22.n2.p99-113.2023
Farid Wajdi, Mohd Sazli Saad
3D printing of free-form objects presents inherent complexity due to their organic and intricate shapes. Designers engage with such objects, considering a range of factors including aesthetics, engineering viability, and ergonomic comfort. This research is focused on achieving the most effective printing parameters for a free-form object utilizing the Digital Light Processing (DLP) technique within a 3D printer. Within this study, a squeezed hexagonal tube-shaped CAD model was employed as an experimental subject, following the principles of the Response Surface Method (RSM). The research delved into the optimization of printing parameters, particularly layer thickness and exposure time, to enhance the dimensional accuracy and surface quality of the free-form model. Two levels were established for each factor: layer thickness was set at 0.06 mm (low) and 0.08 mm (high), while exposure time was tested at 6 s (low) and 8 s (high). The assessment of surface quality involved a qualitative evaluation employing a digital microscope to identify potential defects and imperfections in the print outcomes. The investigation culminated in the identification of the optimal printing parameters: a layer thickness of 0.0753 mm and an exposure time of 7.2143 seconds. This achievement not only enhances the understanding of 3D printing variables in the context of intricate free-form models but also contributes to the broader field of additive manufacturing parameter optimization.
{"title":"Optimizing Surface Finish and Dimensional Accuracy in 3D Printed Free-Form Objects","authors":"Farid Wajdi, Mohd Sazli Saad","doi":"10.25077/josi.v22.n2.p99-113.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n2.p99-113.2023","url":null,"abstract":"3D printing of free-form objects presents inherent complexity due to their organic and intricate shapes. Designers engage with such objects, considering a range of factors including aesthetics, engineering viability, and ergonomic comfort. This research is focused on achieving the most effective printing parameters for a free-form object utilizing the Digital Light Processing (DLP) technique within a 3D printer. Within this study, a squeezed hexagonal tube-shaped CAD model was employed as an experimental subject, following the principles of the Response Surface Method (RSM). The research delved into the optimization of printing parameters, particularly layer thickness and exposure time, to enhance the dimensional accuracy and surface quality of the free-form model. Two levels were established for each factor: layer thickness was set at 0.06 mm (low) and 0.08 mm (high), while exposure time was tested at 6 s (low) and 8 s (high). The assessment of surface quality involved a qualitative evaluation employing a digital microscope to identify potential defects and imperfections in the print outcomes. The investigation culminated in the identification of the optimal printing parameters: a layer thickness of 0.0753 mm and an exposure time of 7.2143 seconds. This achievement not only enhances the understanding of 3D printing variables in the context of intricate free-form models but also contributes to the broader field of additive manufacturing parameter optimization.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.25077/josi.v22.n2.p81-98.2023
Nailul Izzah, A. Sutarto, Ade Hendi, Maslakhatul Ainiyah
With a growing emphasis on cognitive processing in occupational tasks and the prevalence of wearable sensing devices, understanding and managing mental workload has broad implications for safety, efficiency, and well-being. This study aims to develop machine learning (ML) models for predicting mental workload using Heart Rate Variability (HRV) as a representation of the Autonomic Nervous System (ANS) physiological signals. A laboratory experiment, involving 34 participants, was conducted to collect datasets. All participants were measured during baseline, two cognitive tests, and recovery, which were further separated into binary classes (rest vs workload). A comprehensive evaluation was conducted on several ML algorithms, including both single (Support Vector Machine/SVM and Naïve Bayes) and ensemble learning (Gradient Boost and AdaBoost) classifiers and incorporating selected features and validation approaches. The findings indicate that most HRV features differ significantly during periods of mental workload compared to rest phases. The SVM classifier with knowledge domain selection and leave-one-out cross-validation technique is the best model (68.385). These findings highlight the potential to predict mental workload through interpretable features and individualized approaches even with a relatively simple model. The study contributes not only to the creation of a new dataset for specific populations (such as Indonesia) but also to the potential implications for maintaining human cognitive capabilities. It represents a further step toward the development of a mental workload recognition system, with the potential to improve decision-making where cognitive readiness is limited and human error is increased.
随着人们越来越重视职业任务中的认知处理，以及可穿戴传感设备的普及，了解和管理脑力劳动负荷对安全、效率和健康有着广泛的影响。本研究旨在利用心率变异性（HRV）作为自律神经系统（ANS）生理信号的代表，开发预测脑力劳动负荷的机器学习（ML）模型。为了收集数据集，我们进行了一项有 34 名参与者参加的实验室实验。所有参与者都在基线、两项认知测试和恢复期接受了测量，并进一步分为二元类别（休息与工作量）。对几种 ML 算法进行了综合评估，包括单一（支持向量机/SVM 和奈夫贝叶斯）和集合学习（梯度提升和 AdaBoost）分类器，并纳入了选定的特征和验证方法。研究结果表明，与休息阶段相比，大多数心率变异特征在脑力劳动期有显著差异。采用知识领域选择和留一交叉验证技术的 SVM 分类器是最佳模型（68.385）。这些发现凸显了通过可解释的特征和个性化方法预测脑力劳动负荷的潜力，即使模型相对简单。这项研究不仅有助于为特定人群（如印度尼西亚）创建一个新的数据集，而且对保持人类认知能力具有潜在意义。它代表着向开发心理工作量识别系统又迈进了一步，有可能在认知准备有限和人为错误增加的情况下改善决策。
{"title":"Physiological Signals as Predictors of Mental Workload: Evaluating Single Classifier and Ensemble Learning Models","authors":"Nailul Izzah, A. Sutarto, Ade Hendi, Maslakhatul Ainiyah","doi":"10.25077/josi.v22.n2.p81-98.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n2.p81-98.2023","url":null,"abstract":"With a growing emphasis on cognitive processing in occupational tasks and the prevalence of wearable sensing devices, understanding and managing mental workload has broad implications for safety, efficiency, and well-being. This study aims to develop machine learning (ML) models for predicting mental workload using Heart Rate Variability (HRV) as a representation of the Autonomic Nervous System (ANS) physiological signals. A laboratory experiment, involving 34 participants, was conducted to collect datasets. All participants were measured during baseline, two cognitive tests, and recovery, which were further separated into binary classes (rest vs workload). A comprehensive evaluation was conducted on several ML algorithms, including both single (Support Vector Machine/SVM and Naïve Bayes) and ensemble learning (Gradient Boost and AdaBoost) classifiers and incorporating selected features and validation approaches. The findings indicate that most HRV features differ significantly during periods of mental workload compared to rest phases. The SVM classifier with knowledge domain selection and leave-one-out cross-validation technique is the best model (68.385). These findings highlight the potential to predict mental workload through interpretable features and individualized approaches even with a relatively simple model. The study contributes not only to the creation of a new dataset for specific populations (such as Indonesia) but also to the potential implications for maintaining human cognitive capabilities. It represents a further step toward the development of a mental workload recognition system, with the potential to improve decision-making where cognitive readiness is limited and human error is increased.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.25077/josi.v22.n2.p126-141.2023
Yolanda Mega Risma, D. M. Utama
Global energy consumption is a pressing issue and is predicted to continue increasing between 2010 and 2040. Among the various sectors, the industrial sector, particularly manufacturing, is the main driver of this increase. To effectively address this growing problem and support energy conservation efforts, reducing idle time on production-related machines is critical. The No-Idle Permutation Flow Shop Problem (NIPFSP) and, indirectly, the need to reduce energy consumption in manufacturing processes are the driving forces behind this study. The African Vultures Optimization Algorithm (AVOA) and the Ant Lion Optimizer (ALO) are two novel meta-heuristic algorithms designed to achieve this goal. The effectiveness of both AVOA and ALO was rigorously evaluated across three distinct scenarios: small, medium, and large. Statistical analysis, in the form of independent sample t-tests, was employed to compare the performance of these algorithms. We found that, while both algorithms yielded similar results in the small case, AVOA demonstrated a superior capability in optimizing the NIPFSP in the medium and large cases and, consequently, in curbing energy consumption. This implies that AVOA offers a more promising approach to addressing energy consumption concerns in the manufacturing sector, particularly in scenarios involving medium- to large-scale production processes. The implementation of such innovative meta-heuristic algorithms holds the potential to significantly contribute to global energy conservation efforts while enhancing the efficiency of industrial operations.
{"title":"AVOA and ALO Algorithm for Energy-Efficient No-Idle Permutation Flow Shop Scheduling Problem: A Comparison Study","authors":"Yolanda Mega Risma, D. M. Utama","doi":"10.25077/josi.v22.n2.p126-141.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n2.p126-141.2023","url":null,"abstract":"Global energy consumption is a pressing issue and is predicted to continue increasing between 2010 and 2040. Among the various sectors, the industrial sector, particularly manufacturing, is the main driver of this increase. To effectively address this growing problem and support energy conservation efforts, reducing idle time on production-related machines is critical. The No-Idle Permutation Flow Shop Problem (NIPFSP) and, indirectly, the need to reduce energy consumption in manufacturing processes are the driving forces behind this study. The African Vultures Optimization Algorithm (AVOA) and the Ant Lion Optimizer (ALO) are two novel meta-heuristic algorithms designed to achieve this goal. The effectiveness of both AVOA and ALO was rigorously evaluated across three distinct scenarios: small, medium, and large. Statistical analysis, in the form of independent sample t-tests, was employed to compare the performance of these algorithms. We found that, while both algorithms yielded similar results in the small case, AVOA demonstrated a superior capability in optimizing the NIPFSP in the medium and large cases and, consequently, in curbing energy consumption. This implies that AVOA offers a more promising approach to addressing energy consumption concerns in the manufacturing sector, particularly in scenarios involving medium- to large-scale production processes. The implementation of such innovative meta-heuristic algorithms holds the potential to significantly contribute to global energy conservation efforts while enhancing the efficiency of industrial operations.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":"28 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138995623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.25077/josi.v22.n2.p114-125.2023
Giovano Alberto, Carles Sitompul
In today's travel and tourism landscape, the role of travel agents has become increasingly complex as they are challenged to explore a variety of potential destinations. More specifically, the complicated task of planning itineraries that truly satisfy travellers puts travel agents in a crucial role, increasing the complexity of itinerary planning. This complexity is compounded not only by the multitude of possible destinations, but also by non-negotiable constraints such as cost and time. To address these challenges, the orienteering problem represents a fundamental mathematical model that provides a theoretical basis for understanding the nuanced difficulties faced by travel agents.This study ventures into a novel iteration of the orienteering problem, with a particular focus on optimizing travel satisfaction based on length of stay. A notable aspect of this variant is the inclusion of time and cost constraints in the route determination process. Using an integer programming model, the satisfaction scores for each location are described by a diminishing returns function linked to length of stay, while the costs associated with each location follow a linear function influenced by the same parameter. The application of this model is in a hypothetical scenario with 32 nodes, with the calculations facilitated by the FilMINT solver. A sensitivity analysis examines time and cost constraints and shows their decisive influence on the optimization of travel routes. The results of this research contribute significantly to a strategic framework and provide travel agencies with the opportunity to create itineraries that not only meet practical limits but, more importantly, increase traveller satisfaction.
{"title":"Dynamic Scoring and Costing in the Orienteering Problem: A Model Based on Length of Stay","authors":"Giovano Alberto, Carles Sitompul","doi":"10.25077/josi.v22.n2.p114-125.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n2.p114-125.2023","url":null,"abstract":"In today's travel and tourism landscape, the role of travel agents has become increasingly complex as they are challenged to explore a variety of potential destinations. More specifically, the complicated task of planning itineraries that truly satisfy travellers puts travel agents in a crucial role, increasing the complexity of itinerary planning. This complexity is compounded not only by the multitude of possible destinations, but also by non-negotiable constraints such as cost and time. To address these challenges, the orienteering problem represents a fundamental mathematical model that provides a theoretical basis for understanding the nuanced difficulties faced by travel agents.This study ventures into a novel iteration of the orienteering problem, with a particular focus on optimizing travel satisfaction based on length of stay. A notable aspect of this variant is the inclusion of time and cost constraints in the route determination process. Using an integer programming model, the satisfaction scores for each location are described by a diminishing returns function linked to length of stay, while the costs associated with each location follow a linear function influenced by the same parameter. The application of this model is in a hypothetical scenario with 32 nodes, with the calculations facilitated by the FilMINT solver. A sensitivity analysis examines time and cost constraints and shows their decisive influence on the optimization of travel routes. The results of this research contribute significantly to a strategic framework and provide travel agencies with the opportunity to create itineraries that not only meet practical limits but, more importantly, increase traveller satisfaction.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":"136 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138965058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.25077/josi.v22.n2.p165-178.2023
Cholida Usi Wardani, S. Abusini, Isnani Darti
The pursuit of efficiency in the business sector is a multifaceted endeavor, extending beyond mere cost reduction to encompass a strategic optimization of operational performance. The enhancement of efficiency is not solely for the benefit of investors or proprietors but is also a concerted effort to maximize resource utilization and minimize waste. This study introduces an integrative approach combining IFTOPSIS and DEA methodologies to deliver a robust efficiency evaluation framework.The fusion of IFTOPSIS's qualitative analysis with DEA's quantitative assessments addresses the complexity of operational performance, providing a balanced evaluation that transcends subjective bias with data-driven insights. IFTOPSIS articulates decision-makers' preferences in uncertain scenarios, assigning weights to criteria, while DEA discriminates between efficient and inefficient operational units. This confluence of methods is applied to the assessment of inpatient healthcare units—a sector that has traditionally relied on patient-centric evaluations, neglecting the comprehensive review of resource deployment. The results of this amalgamated approach reveal dimensions of operational efficiency previously unexplored, offering stakeholders a data-enriched foundation for strategic decision-making. The study's findings have significant implications for the healthcare industry, providing a template for resource evaluation that could inform policy and drive improvements in patient care services.
商业部门追求效率是一项多方面的努力，不仅仅是降低成本，还包括从战略上优化经营业绩。提高效率不仅仅是为了投资者或经营者的利益，也是最大限度地利用资源和减少浪费的共同努力。IFTOPSIS 的定性分析与 DEA 的定量评估相结合，解决了运营绩效的复杂性问题，提供了一种平衡的评估方法，超越了主观偏见，具有数据驱动的洞察力。IFTOPSIS 阐明决策者在不确定情况下的偏好，为标准分配权重，而 DEA 则区分高效和低效的业务单位。这两种方法的结合被应用于住院医疗单位的评估--该行业传统上依赖于以病人为中心的评估，而忽视了对资源配置的全面审查。这种综合方法的结果揭示了以前未曾探索过的运营效率层面，为利益相关者的战略决策提供了丰富的数据基础。研究结果对医疗保健行业具有重要意义，为资源评估提供了一个模板，可为政策提供依据，并推动患者护理服务的改善。
{"title":"Synergizing IFTOPSIS and DEA for Enhanced Efficiency Analysis in Inpatient Units","authors":"Cholida Usi Wardani, S. Abusini, Isnani Darti","doi":"10.25077/josi.v22.n2.p165-178.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n2.p165-178.2023","url":null,"abstract":"The pursuit of efficiency in the business sector is a multifaceted endeavor, extending beyond mere cost reduction to encompass a strategic optimization of operational performance. The enhancement of efficiency is not solely for the benefit of investors or proprietors but is also a concerted effort to maximize resource utilization and minimize waste. This study introduces an integrative approach combining IFTOPSIS and DEA methodologies to deliver a robust efficiency evaluation framework.The fusion of IFTOPSIS's qualitative analysis with DEA's quantitative assessments addresses the complexity of operational performance, providing a balanced evaluation that transcends subjective bias with data-driven insights. IFTOPSIS articulates decision-makers' preferences in uncertain scenarios, assigning weights to criteria, while DEA discriminates between efficient and inefficient operational units. This confluence of methods is applied to the assessment of inpatient healthcare units—a sector that has traditionally relied on patient-centric evaluations, neglecting the comprehensive review of resource deployment. The results of this amalgamated approach reveal dimensions of operational efficiency previously unexplored, offering stakeholders a data-enriched foundation for strategic decision-making. The study's findings have significant implications for the healthcare industry, providing a template for resource evaluation that could inform policy and drive improvements in patient care services.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.25077/josi.v22.n1.p22-30.2023
Feby Gusti Dendra, E. Amrina, A. S. Indrapriyatna
The definition and function of inventory management reveal the importance of modern industry in formulating policies that regulate the supply of raw materials, semi-finished products, and finished products. Unfortunately, most companies fail to consider the characteristics of their raw materials when determining inventory strategies. Raw materials that are perishable are those that consider their service life and storage time. Inventory management plays a crucial role in supply chain management, especially for perishable raw materials, such as food products. PT X, a food business in Padang, experienced difficulty in meeting the demand for rendang products due to a lack of raw materials. Therefore, this study aims to develop an inventory management model that takes into account the perishable raw materials' expiration time. The model development consists of three stages: model development design, inventory model formulation, and model testing. The proposed model resulted in a storage time interval of five days and an optimal order quantity of 34 kg of meat with a safety stock of 14 kg. Implementing this model led to lower total inventory costs for PT X than the actual conditions of the company. The total inventory cost obtained using this model is Rp279,797,822. This study emphasizes the importance of considering the characteristics of raw materials in determining inventory strategies to optimize inventory management effectively and efficiently. The study's findings can serve as a reference for other food businesses encountering similar inventory management challenges in the perishable food industry.
{"title":"Inventory Control Model of Beef for Rendang Products","authors":"Feby Gusti Dendra, E. Amrina, A. S. Indrapriyatna","doi":"10.25077/josi.v22.n1.p22-30.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n1.p22-30.2023","url":null,"abstract":"The definition and function of inventory management reveal the importance of modern industry in formulating policies that regulate the supply of raw materials, semi-finished products, and finished products. Unfortunately, most companies fail to consider the characteristics of their raw materials when determining inventory strategies. Raw materials that are perishable are those that consider their service life and storage time. Inventory management plays a crucial role in supply chain management, especially for perishable raw materials, such as food products. PT X, a food business in Padang, experienced difficulty in meeting the demand for rendang products due to a lack of raw materials. Therefore, this study aims to develop an inventory management model that takes into account the perishable raw materials' expiration time. The model development consists of three stages: model development design, inventory model formulation, and model testing. The proposed model resulted in a storage time interval of five days and an optimal order quantity of 34 kg of meat with a safety stock of 14 kg. Implementing this model led to lower total inventory costs for PT X than the actual conditions of the company. The total inventory cost obtained using this model is Rp279,797,822. This study emphasizes the importance of considering the characteristics of raw materials in determining inventory strategies to optimize inventory management effectively and efficiently. The study's findings can serve as a reference for other food businesses encountering similar inventory management challenges in the perishable food industry.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42839877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.25077/josi.v22.n1.p31-37.2023
I. Noor, Nur Ambulani
The biggest challenge in developing digital talent in tertiary institutions is viewing digital reform as a massive entity. Therefore, it is rare to focus on the values of developing digital talent for existing education personnel. Using a growth theory mindset, the research focuses on Working Period, Performance, and Qualification, to see the relationship with Talented education staff. The research uses a sequential explanatory design. The sample consisted of 29 ASNs in one of the faculties of a state university in Indonesia, with random sampling using the online Sample Size Calculator. Questionnaire data were analyzed by SPSS, while interviews with NVivo-12 Pro. The results reveal that both the Working Period, Qualification, and Performance variables correlate with the Talented education of staff. The direction of the relationship also has a positive (+) value. However, qualitative analysis revealed that the activities carried out were more directed at fulfilling the main duties and functions. Behind that, the biggest challenge for them is when dealing with students, who generally come from the digital generation. Therefore, digital reform in higher education also pays attention to developing digital talent for education staff.
{"title":"The Relationship between Work Experience, Qualifications, Performance, and Staff Perception of Digital Talent in the Workplace","authors":"I. Noor, Nur Ambulani","doi":"10.25077/josi.v22.n1.p31-37.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n1.p31-37.2023","url":null,"abstract":"The biggest challenge in developing digital talent in tertiary institutions is viewing digital reform as a massive entity. Therefore, it is rare to focus on the values of developing digital talent for existing education personnel. Using a growth theory mindset, the research focuses on Working Period, Performance, and Qualification, to see the relationship with Talented education staff. The research uses a sequential explanatory design. The sample consisted of 29 ASNs in one of the faculties of a state university in Indonesia, with random sampling using the online Sample Size Calculator. Questionnaire data were analyzed by SPSS, while interviews with NVivo-12 Pro. The results reveal that both the Working Period, Qualification, and Performance variables correlate with the Talented education of staff. The direction of the relationship also has a positive (+) value. However, qualitative analysis revealed that the activities carried out were more directed at fulfilling the main duties and functions. Behind that, the biggest challenge for them is when dealing with students, who generally come from the digital generation. Therefore, digital reform in higher education also pays attention to developing digital talent for education staff.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49354344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.25077/josi.v22.n1.p9-21.2023
Noufal Zhafira, T. S. Dewayana, D. Sugiarto
Coal transshipment necessitates efficient and prompt execution, devoid of any delays or work-related accidents. Numerous events during the transshipment process have the potential to disrupt operations and pose substantial risks. This research aims to examine the risks associated with coal transshipment by leveraging ISO 31000:2018 as the risk analysis framework. Additionally, it seeks to prioritize risk mitigation strategies employing the Techniques for Other Preferences by Similarity to Ideal Solutions (TOPSIS) methodology. Data collection for this study involved surveys and expert discussions to comprehensively analyze all risks by ISO 31000:2018 guidelines. The findings were then visualized through the use of a fishbone diagram, which facilitated the identification and understanding of the generated risks. The analysis revealed several threats that could impact the coal transshipment process. These major threats include natural disasters, equipment failures, shipping accidents, health risks for workers, fire hazards, operational delays, inefficient loading and unloading processes, and transportation accidents. The proposed mitigation strategies such as designing SOPs, developing emergency response plans, implementing safety measures, providing training, conducting risk assessments, and ensuring equipment maintenance, are academically supported and practical in their application. However, challenges such as financial constraints, resistance to change, and the dynamic nature of the process need to be overcome for effective implementation. Organizations can enhance safety and operational efficiency in coal transshipment by carefully managing resources, engaging stakeholders, and continuously evaluating and improving strategies. Overall, the proposed strategies offer a feasible and proactive means to mitigate threats and promote a safer and more efficient transshipment process.
{"title":"Risk Mitigation Strategy for Coal Transshipment","authors":"Noufal Zhafira, T. S. Dewayana, D. Sugiarto","doi":"10.25077/josi.v22.n1.p9-21.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n1.p9-21.2023","url":null,"abstract":"Coal transshipment necessitates efficient and prompt execution, devoid of any delays or work-related accidents. Numerous events during the transshipment process have the potential to disrupt operations and pose substantial risks. This research aims to examine the risks associated with coal transshipment by leveraging ISO 31000:2018 as the risk analysis framework. Additionally, it seeks to prioritize risk mitigation strategies employing the Techniques for Other Preferences by Similarity to Ideal Solutions (TOPSIS) methodology. Data collection for this study involved surveys and expert discussions to comprehensively analyze all risks by ISO 31000:2018 guidelines. The findings were then visualized through the use of a fishbone diagram, which facilitated the identification and understanding of the generated risks. The analysis revealed several threats that could impact the coal transshipment process. These major threats include natural disasters, equipment failures, shipping accidents, health risks for workers, fire hazards, operational delays, inefficient loading and unloading processes, and transportation accidents. The proposed mitigation strategies such as designing SOPs, developing emergency response plans, implementing safety measures, providing training, conducting risk assessments, and ensuring equipment maintenance, are academically supported and practical in their application. However, challenges such as financial constraints, resistance to change, and the dynamic nature of the process need to be overcome for effective implementation. Organizations can enhance safety and operational efficiency in coal transshipment by carefully managing resources, engaging stakeholders, and continuously evaluating and improving strategies. Overall, the proposed strategies offer a feasible and proactive means to mitigate threats and promote a safer and more efficient transshipment process.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49311345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.25077/josi.v22.n1.p69-80.2023
P. Karningsih, Winda Puspitasari, M. Singgih
The company has always prioritized cost reduction. In this study, the researchers aimed to decrease maintenance costs by actively eliminating expensive non-value-added processes. The study employed Process and Time Driven Activity Based Costing to integrate cost with the activities performed. By conducting maintenance value stream mapping, the researchers identified various forms of waste, such as centralized maintenance, ineffective data management, poor inventory management, inadequate maintenance, under-utilization of resources, and waiting time for maintenance resources. Several alternative improvement options were proposed, and the Pugh method was used to compare and select the most promising alternatives or combinations of alternatives. The third alternative, which involves conducting internal training and implementing standard operating procedures for maintenance technicians, supervisors, and machine operators, as well as integrating an IT system for maintenance and creating an equipment and spare parts inventory database, was chosen as the highest-ranking option. The results showed that this approach reduced processing time for administrative activities, lowered corrective maintenance costs, and improved maintenance efficiency for both preventive and corrective maintenance.
{"title":"Cost-Integrated Lean Maintenance to Reduce Maintenance Cost","authors":"P. Karningsih, Winda Puspitasari, M. Singgih","doi":"10.25077/josi.v22.n1.p69-80.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n1.p69-80.2023","url":null,"abstract":"The company has always prioritized cost reduction. In this study, the researchers aimed to decrease maintenance costs by actively eliminating expensive non-value-added processes. The study employed Process and Time Driven Activity Based Costing to integrate cost with the activities performed. By conducting maintenance value stream mapping, the researchers identified various forms of waste, such as centralized maintenance, ineffective data management, poor inventory management, inadequate maintenance, under-utilization of resources, and waiting time for maintenance resources. Several alternative improvement options were proposed, and the Pugh method was used to compare and select the most promising alternatives or combinations of alternatives. The third alternative, which involves conducting internal training and implementing standard operating procedures for maintenance technicians, supervisors, and machine operators, as well as integrating an IT system for maintenance and creating an equipment and spare parts inventory database, was chosen as the highest-ranking option. The results showed that this approach reduced processing time for administrative activities, lowered corrective maintenance costs, and improved maintenance efficiency for both preventive and corrective maintenance.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42776715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.25077/josi.v22.n1.p1-8.2023
R. Primadasa, Bellachintya Reira Christata
This paper tries to model agile supply chain management performance indicators in the palm oil industry. The interpretative Structural Modeling (ISM) method is used to find the relationship between these indicators. The ISM stages begin with identifying indicators, compiling contextual relationships, compiling reachability matrices, compiling level partitions, compiling digraphs, and compiling ISM models. Then MICMAC analysis is used to group each of these indicators into four categories based on their driving power and dependence power. In this study, 16 hands of agile supply chain management in the palm oil industry were obtained, of which the four-level ISM model could be constructed. Two indicators are at level 4, six hands are at level 3, three indicators are at level 2, and five indicators are at level 1. Meanwhile, through MICMAC analysis, five indicators are found in the independent indicators category, six hands are in the linkage indicator category, four indicators are included in the dependent indicator category, and one indicator is in the autonomous indicator category. This research can be used by managers in the palm oil industry who want to increase agility in their supply chain. In general, indicators at level 4 can affect indicators at level 3, and so on. So that management can start fixing the indicators at level 4 first. In addition, indicators that have a driving power value in MICMAC analysis can be prioritized to improve their performance.
{"title":"Interrelationship Performance Indicators Model of Agile Supply Chain Management in Palm Oil Industry","authors":"R. Primadasa, Bellachintya Reira Christata","doi":"10.25077/josi.v22.n1.p1-8.2023","DOIUrl":"https://doi.org/10.25077/josi.v22.n1.p1-8.2023","url":null,"abstract":"This paper tries to model agile supply chain management performance indicators in the palm oil industry. The interpretative Structural Modeling (ISM) method is used to find the relationship between these indicators. The ISM stages begin with identifying indicators, compiling contextual relationships, compiling reachability matrices, compiling level partitions, compiling digraphs, and compiling ISM models. Then MICMAC analysis is used to group each of these indicators into four categories based on their driving power and dependence power. In this study, 16 hands of agile supply chain management in the palm oil industry were obtained, of which the four-level ISM model could be constructed. Two indicators are at level 4, six hands are at level 3, three indicators are at level 2, and five indicators are at level 1. Meanwhile, through MICMAC analysis, five indicators are found in the independent indicators category, six hands are in the linkage indicator category, four indicators are included in the dependent indicator category, and one indicator is in the autonomous indicator category. This research can be used by managers in the palm oil industry who want to increase agility in their supply chain. In general, indicators at level 4 can affect indicators at level 3, and so on. So that management can start fixing the indicators at level 4 first. In addition, indicators that have a driving power value in MICMAC analysis can be prioritized to improve their performance.","PeriodicalId":30702,"journal":{"name":"Jurnal Optimasi Sistem Industri","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49162294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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