SINTA 4 SINCE MARCH 21ST, 2025 Jurnal Rekayasa Sistem Industri (JRSI), which was founded on May 29, 2007, is a scientific journal maintained by the Universitas Katolik Parahyangan in Bandung - Indonesia. JRSI addresses the latest trends as stated in their focus and scope. Since June 2016 we are a proud member of CROSSREF. The DOI prefix of Jurnal Rekayasa Sistem Industri is 10.26593/jrsi. Therefore, all articles published by Jurnal Rekayasa Sistem Industri will have a unique DOI number. Since January 2019, JRSI proud to be a member of Directory of Open Access Journal (DOAJ). JRSI is ready to receive articles from researchers, lecturers, students, every day for a year and publish twice a year in April and October. One JRSI volume is divided into two editions, published in April and October each year. Articles must be written in the Indonesian language OR English, and abstracts must be in English and Indonesian language. All researchers that working on our focus and scope were invited to submit their articles to JRSI (please see Author guidelines). All articles that comply with our publication ethics will be reviewed by the editor based on the research area and format. If the article complies with the scope of the JRSI research, the paper will be assigned to two reviewers using the double-blinded review system. The authors can see some criticisms and comments about their articles through our OJS system. After an author has finished revising, the article then The Editor will check the similarity of the article using ithenticate similarity check and then the article will be published in the next JRSI volume. All authors must read and agree with our Plagiarism & Retraction Policy before sending their articles. There is no fee charged for the author for the submission, reviewing, and publication process. JRSI (Jurnal Rekayasa Sistem Industri) is an open-access journal that is a double blind peer-reviewed published regularly twice a year (April and October) by Industrial Engineering Department of Parahyangan Catholic University. JRSI welcomes research and review articles in both Bahasa Indonesia and English on the various industrial engineering topics. Online ISSN : 2339-1499 Distribution : Open Access Frequency : 2 (two) issues per year (April and October) DOI : 10.26593/jrsi Country : Indonesia Submit Manuscript Now! Indexed by
Consumer Intention to Use More Environmentally Friendly Fuel Based on UTAUT2 with Consideration of Sustainability Aspects
This research aims to identify the factors influencing the intention to use more environmentally friendly fuel for private vehicles. According to the regulations of the Ministry of Energy and Mineral Resources (ESDM), environmentally friendly fuel is fuel with a minimum octane rating of 91 or a minimum cetane rating of 51. Although the Indonesian government has encouraged the public to use environmentally friendly fuel, the public has not yet made this fuel their primary choice. This study examines the intention to adopt environmentally friendly fuel based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. In line with the characteristics of environmentally friendly fuel, this research enriches the UTAUT2 model with a sustainability perspective through the variables of environmental knowledge and environmental friendliness, which are the theoretical contributions of the study. The developed research model was evaluated using Partial Least Squares Structural Equation Modelling (PLS-SEM) based on 129 data collected from residents of major cities in Indonesia who refuel their vehicles. The results of this study found that environmental knowledge, habit, and price value significantly influence the public's intention to use environmentally friendly fuel. This research also offers practical contributions for stakeholders in the form of recommendations such as socialization and economic promotion to increase the use of more environmentally friendly fuel in Indonesia.
Copyright (c) 2025 Jurnal Rekayasa Sistem Industri
Dynamic System Modeling to Enhance Enrollment at Private University XYZ
Higher education is an important level of education for society. According to information, private universities (PTS) are the most prevalent in Indonesia. This results in intense competition among PTS, presenting challenges in attracting prospective students, and necessitating effective strategies to reach these students. XYZ University is a campus with advantages such as active learning, reputable faculty, boarding life, comprehensive facilities, and a scenic location. However, the number of applicants to this PTS has fluctuated in recent years. This study aims to develop a dynamic system simulation model to increase the number of applicants. This modeling allows for the analysis of related variables and the side effects of policies. The study's results are expected to provide policy recommendations and strategies to boost the number of applicants. Based on the modeling conducted, four scenarios were tested against the existing simulation data. The simulation results showed that Scenario 2 produced the highest average number of applicants. This scenario involves promotional costs, promotional effectiveness, tuition fees, and reputation in increasing the number of applicants. Policy recommendations to consider include optimizing promotional costs by analyzing and evaluating current promotions, utilizing cost-effective promotions such as social media, and improving webometric rankings in terms of publication and research development to enhance the reputation of the PTS.
Soft TQM’s Effect on Employee Job Satisfaction and Performance at An Indonesian Oil and Gas Company
The rapid economic and industrial expansion has led to increased global corporate competitiveness, forcing organizations to constantly improve their effectiveness and sustainability. Total Quality Management (TQM) is recognized as a process that enhances individual and organizational performance, competitive advantage, and customer satisfaction. Despite its recognized value, the implementation of soft TQM practices remains underexplored in high-risk and heavily regulated sectors such as the oil and gas industry, especially within the Indonesian. PT XYZ, an oil and gas company in Indonesia, has implemented TQM. However, the company continues to face operational issues including unmet departmental targets and the lack of implementation of essential work-related innovations. This study investigates the influence of soft TQM on Employee Job Satisfaction (EJS) and Employee Performance (EP), and examines EJS as a mediating variable. Data were collected through questionnaires using a Likert scale and analyzed using PLS-SEM with SmartPLS 4. The results indicate that soft TQM significantly and positively affects both EJS and EP, and that EJS significantly mediates the relationship between soft TQM and EP. The study contributes to TQM theory by extending its application to an underrepresented industrial and national context, and by emphasizing the importance of human-centered practices in improving individual performance outcomes. It also highlights the need for tailored quality strategies to address challenges such as workforce diversity, operational complexity, and innovation implementation in the oil and gas sector.
Supply Chain Risk Analysis Using the House of Risk (HOR) Method at CV. Padaidi
Business competition today does not only occur between individual companies, but also between business networks. Companies are required to not only produce quality products, but also provide significant added value and implement the right strategy to survive in the increasingly fierce competition. An effective strategy includes various aspects, such as planning, production, and delivery of products to consumers, all of which are important parts of supply chain management. This research was conducted at CV. Padaidi Center for Small and Medium Industries (IKM) Furniture Morowali, Central Sulawesi, which is engaged in the production of furniture, including chairs, tables, cabinets, and other products, with the aim of meeting consumer needs and remaining competitive. To achieve this goal, the company needs good supply chain strategy planning, including the identification of risks that may arise and their effective management. This research uses the House of Risk (HOR) method to determine priorities in risk management strategies, while the identification of business activities is carried out using the Supply Chain Operation Reference (SCOR) method, which is then continued with risk analysis in each activity. Not many studies have combined the HOR and SCOR methods, and the novelty of this research lies in the combination of the two methods, especially in the IKM Furniture sector. The research identified 19 risk events and 20 risk agents that can affect the smoothness of the supply chain. The results of the research can contribute to designing more effective risk mitigation strategies, in order to improve the resilience and efficiency of the company's supply chain.
Improving Service Efficiency in XYZ Creative Agency Using Lean Six Sigma and SERVQUAL Methods
This study discusses the urgency of improving operational efficiency and service quality in the creative industry by addressing theoretical gaps in the application of Lean Six Sigma (LSS) and SERVQUAL methodologies. XYZ Creative Agency, a provider of social media management services, was selected as a case study to emphasize the practical contributions of the research. The main challenges include service delivery delays and insufficient service assurance. The Lean Six Sigma and SERVQUAL methods were applied to analyze and resolve these issues. The SERVQUAL analysis results revealed positive gaps in the assurance dimension (+0.0615) and the reliability dimension (+0.0154), indicating the need to enhance information clarity, client trust, and service timeliness. Value Stream Mapping (VSM) identified that delays primarily occurred during the content approval stage, while Fishbone Diagram analysis uncovered root causes such as inadequate team coordination, ineffective communication, and underutilized technology. Implemented solutions included the use of a digital project management platform to improve process transparency and efficiency, regular employee training to enhance competencies, and the development of a client feedback system. The DMAIC approach employed in Lean Six Sigma proved effective in designing data-driven solutions to improve operational efficiency and service quality. The implementation of these solutions is expected to reduce delays, enhance client satisfaction, and strengthen XYZ’s competitiveness in the creative industry.
A Preliminary Study to Develop a University Sustainability Assessment for Indonesia
As a way to achieve sustainable development, it is important to develop a tool for assessing sustainability of Indonesian universities. There is one tool created by an Indonesian university, which have been utilized by 1,183 universities worldwide. However, the participation of Indonesian universities in sustainability assessment using this tool is considered very low, only 3.12% or about 145 universities in Indonesia. This statistic calls for an effort to develop a new assessment tool that accommodates the context of Indonesian universities. The objective of this research is to develop a sustainability assessment tool that is effective, relevant with the context of Indonesian universities and includes a data input system that is simple to use. The research involves identifying relevant sustainability dimensions, determining indicator criteria suitable for Indonesian context, designing easy data input, and evaluating the validity and reliability of the tool. This study uses a literature review of 29 current measuring tools used globally, which revealed four primary areas (i.e. environment, economics, education, and social). According to this preliminary study, the typical measurement tool averagely has forty indicators. Moreover, it is observed that current tools have some unsuitable indicators to Indonesian context (i.e. infrastructure, environment, and information). This study has streamlined the tool to three primary areas (i.e. environment, social, and education) and 18 assessment indicators. As a follow up study, expert talks, pairwise comparison analysis, and the design and testing of the sustainability assessment tool will be carried out.
Proposed Route for LPG Distribution Using Dijkstra's Algorithm and Genetic Algorithm on CGVRP Model
Determining the route of distribution of goods for companies is an important aspect to consider. The distribution of 3 kg LPG gas at one of the companies in Bandung City does not yet have an optimal route. However, in previous research, a shorter route has been obtained with the Sweep algorithm, which is 118.85 km. The research continued using the Cluster Generalized Vehicle Routing Problem (CGVRP) model with the Dijkstra and Genetics algorithms. CGVRP is the determination of the shortest route using customer clusters. Dijkstra's algorithm is the determination of the route between 2 points from the starting point to the destination point. The result of the distance calculation with the Djkstraa algoritma is 114.779 km. Genetic Algorithm is the determination of the shortest route by reducing the attributes that are less dominant. The result of the distance calculating with Genetic Algorithm is 112 km. This shows a reduction in the total distribution mileage of 6.85 km compared to the completion of the Sweep algorithm in previous studies. The amount of this reduction is large enough to save the company's costs by 5.76%.
Implementation of Hazard Analysis Critical Control Point (HACCP) in a Shrimp Crackers Production SME
Food quality is very important so that food processing must be done properly to ensure food safety, namely by implementing the HACCP system. HACCP is often considered a complex system so that not many companies use it. This study aims to prevent hazards that may arise using the HACCP system and evaluate the quality control of shrimp crackers to reduce defective products.. This study uses a case study approach to a small and medium-sized company that produces raw shrimp crackers. Data were collected through literature reviews, interviews, and observations. The techniques used are quality control, Good Manufacturing Practices – GMP, Sanitation Standard Operating Procedure – SSOP, and Hazard Analysis Critical Control Point – HACCP. The results of the quality control analysis show that products that are included in the Not Good category have the characteristics of being incomplete, untidy, clean, not uniform, and of uneven thickness. The GMP & SSOP analysis results show that this company is at level IV, and is included in the "Unfit" category and HACCP analysis show that there are three processes included in the Critical Control Point (CCP), namely storage of raw and packaging materials, drying, and storage of finished materials. Suggestions for improvement are this company needs to pay more attention to quality control, improves the implementation of GMP and SSOP so that they can reach Level I in GMP and the "Meet" category in SSOP, and only then can implement the HACCP plan.
Design of an Aren Sap Processing Tool for Aren Sap Farmers in Kiarajangkung Village, Tasikmalaya Regency
Indonesia is an archipelagic country rich in biodiversity, including various types of plants that provide important natural resources for the people's basic and economic needs. One of these resources is Hasil Hutan Bukan Kayu (HHBK), such as brown sugar, which is produced from palm sap. The simple and basic palm sap processing method inspired this research to design processing tools that can improve product quality and efficiency for palm sap farmers in Kiarajangkung Village, Tasikmalaya Regency. The product design process began by conducting interviews to identify the farmers' needs. It was found that farmers needed three tools: a furnace for boiling palm sap, a pourer, and a palm sap mold. Specifications for these three processing tools were sought to meet the farmers needs using the House of Quality (HOQ) method. The next stage was concept generation, where six concepts were created for each of the three processing tools. Each concept was tested, and to narrow down the options, two concepts were chosen for the boiling furnace, three for the pourer, and three for the palm sap mold. From these, the best concept was selected and developed into a prototype. The processing tool prototype was designed using Solidworks software before being tested in real conditions. Next, a physical prototype was made, which was later tested by sap farmers. The prototype was tested using the functionality testing method. From the results of the prototype trials, it was found that the processing tool prototype successfully met several success indicators, with some refinements needed for the tools.
Influences of Exposure Time and Body Posture on Cybersickness with Skin Conductance Measurement in Virtual Reality
Cybersickness is a nausea, dizziness, and losing balance while using VR. Cybersickness is caused by exposure time and the body posture of the VR’s user that until now there are still differences in research results regarding the effects on cybersickness. Therefore, this study aims to identify the effects on cybersickness and provide appropriate recommendations to reduce cybersickness symptoms. The measurement of research were Galvanic Skin Response as an objective indicator and the Simulator Sickness Questionnaire (SSQ) questionnaire as a subjective indicator. A total of 48 participants will be given the task of playing parkour activities with sitting or standing postures and played for 10 minutes, 20 minutes, or 30 minutes. To determine the effect of exposure time and body posture, were used ANOVA test and the Kruskal-Wallis test. Based on the results, exposure time has an effect on with the maximum effect at 20 minutes which has an average SSQ value of 109,863 (p-value = 0,046 < 0,05). Meanwhile, body posture also affects cybersickness which standing posture has a higher average GSR (13,082 μS) and p-value = 0,002 < 0,05. The recommendations which are given are the duration using VR is no more than 20 minutes and maintain a balanced body posture which can move their heads slowly to so that the level of cybersickness can be reduced.
Design of Automatic Clothing Measurement Based on Arduino For Indonesian Fashion Industry
The Fashion industry in Indonesia is one of the attractive industrial sectors for the creative economy sub-sector. Based on Statistics Indonesia, the GDP at constant prices of the textile and apparel industry amounted to 34.58 Trillion in the second quarter of 2023. However, clothing sales in physical stores have decreased due to online sales. Furthermore, in physical store sales, the dressing room is limited, the clothes being tried on are unhygienic and there are restrictions on the number of trying on clothes. So, it is necessary to design a clothing sizing tool that can determine the size of clothes, maintain hygiene and reduce queuing time when trying on clothes. The design of this tool begins with conducting interviews and identifying the necessary needs. After identifying the necessary needs, proceed with designing an affinity diagram to group needs that have similarities and determine the level of importance. The results of this determination will be designed into tool specifications using the Need-metric matrix and become the basis for developing tool concepts. From these results, a prototype was designed using Arduino, ultrasonic sensor and LCD display. Testing for the tool will pay attention to the performance results of measurement accuracy and usability testing. For the usability testing method, the SUS (System Usability Scale) method is used. From the results of the study, it was found that the performance value of measurement accuracy was 75.76% and the usability testing score was obtained 68. The performance value of measurement accuracy and usability testing still needs to be improved with proposals in the form of clothing requirements during measurement and the use of more automated tools to make it easier to use.
Design of an Ergonomic Ironing Station for Home-Based Laundry Service Providers Using an Anthropometric and Quality Function Deployment Approach
Laundry services are still used by many people, indicated by its existence, especially in office areas and universities. Not only they offer clothes washing but also ironing such that the clothes are ready to wear directly by consumers. Ironing is a process that requires the longest time so that the workload of the operators is heavier than operators in other work stations. As repetitive force is required in controlling the iron, they need supportive facilities to lessen the burden to the body. Moreover, the narrow working space especially for small, medium enterprises (SMEs) does not allow them to take a seat for while working, leading to fatigue and sores. Motivated by this, through this research we designed an ergonomic facility for ironing work station in laundry shops. We employed Quality Function Deployment method for product development that takes what kind of support the customer needs into account, as well as anthropometry approach to ensure the comfort of the user. Design process consists of four common steps of Ulrich and Eppinger, namely planning, concept development, system-level design, and detail design, while the latter step of testing and refinement was not employed as the product is in the form of 3D prototype. The pilot study found complaints from ironing station operators of several stores due to the inadequate facilities. In this research, the design process involved uncovering main requirements along with supporting needs which are then translated into an ergonomic and multifunctional ironing facility for laundry services belonging to SMEs as the user-centric solution. That is, space saving and comfortable for the operators as well as reduce the risk of musculoskeletal disorder.
Implementation of the Quality Function Deployment (QFD) Method to Improve Mixing Machine Battery Cover Products in the Automotive Industry
Manufacturing companies in the injection molding sector supply plastic-based automotive spare parts such as car battery covers. The mixing process at this company is still done manually because the previous mixing machine was not functioning properly. The problem with a mixing machine is that it produces an uneven mixture. Apart from that, the mixing machine does not yet have a component that functions to filter tin flakes that are mixed into the crusher material. This research aims to reduce the percentage of uneven mixing defects and increase the impeller rotation to the maximum in the mixing process. This research uses the Quality Function Deployment (QFD) method combined with the Fishbone diagram method and the 5W+1H method. This research found that uneven mixing defects during the mixing process were dominant in this problem. After analysis, there was a problem with the distribution of impeller rotation, the maximum was only 0.134 m/s or around 60% of the total material mixing. Redesigned improvement solutions for the mixing process by modifying the mixing machine with more sophisticated technology. This research resulted in a reduction in production defects from 9% to 2% and an expansion of impeller rotation in the mixing process, up to a maximum of 0.202m/s or a flatness of around 90%.
Integrating Kansei Engineering and Design with Intent to Enhance Positive Emotional Response and Persuasiveness of User Interface Design
The rise of digitalization has greatly impacted consumer behavior in Indonesia, leading to a significant increase in e-commerce consumption. As businesses compete for market share through digital channels, research has focused on developing methods to create display designs that evoke positive emotions and are persuasive. This study utilized Kansei Engineering (KE) and Design with Intent (DwI) to develop design patterns of user interface that elicit positive emotional responses and are cognitively beneficial. Kansei word data were collected through interviews and user reviews, resulting in five groups of Kansei Word. DwI was then applied to this data to produce a design pattern that enhances positive emotions. The study concludes that KE and DwI are effective in enhancing users' positive emotional responses and experiences, despite the implementation complexities. The integration of these two methods effectively identifies emotional needs and formulates appropriate design patterns to fulfill those needs. However, further research is needed to explore other factors that influence emotional responses, such as brand image, product price, and user reviews. It is important to note that while product design is important, other aspects of business strategy also require attention.
Design of a Congregational Prayer Bench at Saint John the Evangelist Catholic Church in Kudus Using an Ergonomic Approach
The church is a place of worship for Christians. Its presence is expected to provide both physical and spiritual tranquility. To achieve this, church facilities must strive to offer comfort to their users, such as the congregation's prayer benches. However, some of these prayer benches fail to provide sufficient comfort because, historically, church bench designs are relics from the past, dating back to when the church was first established, and did not take comfort into account during their design. This is also the case at the Catholic Church of St. John the Evangelist in Kudus, where the congregation's prayer benches are still the original design from when the church was founded. As a result, there have been several complaints about the discomfort from users. The method used in this study employs an ergonomic approach to redesign the congregation's prayer benches at the Catholic Church of St. John the Evangelist in Kudus. Anthropometric data used to design the prayer benches were gathered from Javanese and Chinese ethnic groups, both male and female. The results of the study yielded a design for the prayer benches at the Catholic Church of St. John the Evangelist in Kudus, with the following dimensions: prayer bench length = 334.96 cm; bench width = 43.80 cm; bench height = 39.2 cm; shoulder rest height = 47.53 cm; and prayer handrest height = 60.17 cm. Another outcome of this study is the implication for the church congregation, which is an increased perception of comfort in the design of the prayer benches through the ergonomic approach.
Application of the Critical Path Method (CPM) to Improve Efficiency in C-Check Maintenance of Boeing 737-500 Aircraft (PK-NAS) (A Case Study at PT. Merpati Maintenance Facility)
Turn Around Time (TAT) in C-Check maintenance activities is a problem that often occurs in aircraft maintenance service organizations because it requires large operational costs for technicians, and there are losses due to waiting time for aircraft operations during maintenance. This research compares company TAT with TAT using the Critical Path Method (CPM) and the percentage of man-hours efficiency from calculating the CPM method. The research object and data were collected at the PT Merpati Maintenance Facility. The types and sources of data used in research are primary and secondary. The data analysis techniques used are Turn Around Time (TAT) planning calculations and the Critical Path Method (CPM) method, as well as analyzing calculations that have been carried out using Microsoft Excel. Based on the research results, it was found that the difference in results between company planning was 18.56 or 19 work days and planning using the CPM method was 16.94 or 17 work days, so that you get more efficient time for 2 work days in carrying out C-Check maintenance with a percentage of the man hours efficiency formula of 0.087%.
Application of the Lightning Search Algorithm with 2-Opt Local Search for Solving the Asymmetric Traveling Salesman Problem
The Asymmetric Traveling Salesman Problem (ATSP) is an optimization problem where a "salesman" must visit several cities in a single trip. In the ATSP, the distance traveled from city i to j differs from the distance from city j to i. The goal of the ATSP is to minimize the total distance traveled by the "salesman." In this study, the Lightning Search Algorithm (LSA) and the 2-Opt local search algorithm are used to find solutions for the ATSP. LSA is a metaheuristic algorithm inspired by the process of lightning propagation to the earth's surface. 2-Opt is a local search algorithm that can manipulate routes to produce better solutions. This research aims to design LSA with 2-Opt for solving the ATSP and to identify the parameters that influence the ATSP solution. Three parameters are used in this study: maximum channel time (max_ctime) and forking probability (fork_prob), which are responsible for the forking phenomenon, and Boundaries (Bound), which define the solution space. ANOVA testing was conducted on 8 parameter combinations implemented on 5 ATSP cases from TSPLIB: BR17, FTV33, FTV44, FTV55, and FTV70 to determine the best parameter values. The ANOVA results show that the Bound parameter affects the solution in the FTV33, FTV44, and FTV70 cases, while the max_ctime parameter affects the solution in the FTV55 case. Based on the determined parameter values, the LSA with 2-Opt was re-implemented on the five ATSP cases. The results show that the LSA with 2-Opt was able to find the best-known solution for the BR17 case but was unable to find the best-known solution for the other cases.
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Machine Learning for Quality Control in Traditional Textile Manufacturing
This research is centered on the practical implementation of machine learning and computer vision technologies to enhance production quality control within the traditional textile industry. The traditional textile sector, known for labor-intensive practices, has slowly adapted to digital transformation. We present a practical case study from Bandung, Indonesia, to validate the effectiveness of our approach in real-world textile manufacturing. By emphasizing machine learning and computer vision, this research narrows the gap between traditional textile practices and digitalization, offering tailored solutions for manufacturers seeking to excel in today's rapidly changing global market. The findings provide valuable insights into the challenges and opportunities of using machine learning and computer vision for production quality control in traditional textile manufacturing. The machine learning models in the study showed good accuracy, ranging from 75% to 100% under various lighting conditions in real-world textile manufacturing environments, confirming their suitability for practical quality control applications.
quality control, traditional textile industry, machine learning, labor-intensive, digitalization
Optimizing Human Resources Allocation in Bank XYZ: A Simulation-Based Approach During the COVID-19 Pandemic
In 2020 Covid-19 Pandemic strikes the whole country. It forces Organization to change their work habits from Work from Office (WFO) to Work from Home (WFH). It is also triggered by Indonesia Government policy to keep Social Distancing and start Work from Home (WFH). Bank XYZ response by change their working policy to allow employee Work from Office and Work from Home (Hybrid). Then each employee has a different work schedule every week based on their position and Line Manager discretion. Change of amount employee who work from office affects its performance obviously, especially operational function in this case HR Data Management Function. Bank XYZ has not make a further assessment, planning or working simulation about the optimal number of WFO employees yet. By direct observation, processing time data measurement, and memo arrival time data measurement, we make a model simulation based on Arena Software to find most suggested number of WFO employee. The simulation result shows that 7 employees is the best employee number consisting of 1 Team Lead, 1 Analyst, 1 Analyst Assistant, 2 Administrator and 2 Archive Personnel. This number is less than existing employee number before, 14 employees.
Arena, Human Resource Planning, Simulation, WFH, WFO
Proactive Manufacturing Strategy for Managing the Multiproduct Production Plan
The case study focuses on a multi-product company in Indonesia that aims to develop a proactive manufacturing strategy to tackle production disruptions caused by process uncertainty. Data from 30 periods are analyzed to evaluate the company's weekly production plan performance, revealing consistent quantity fulfillment but significant discrepancies in the types of products produced compared to the plan. Process uncertainty, especially regarding quality, leads to disruptions such as uneven and inadequate material supplies. Statistical Process Control (SPC) tools, like Pareto analysis, are used to identify priority quality issues, forming the basis for Fault Tree Analysis (FTA) to trace root causes and determine intervention points. Each machine's limited set of valves and pipes poses challenges for thorough cleaning during downtime and quality management outside working hours. Introducing backup valves and pipes per machine can mitigate these issues and improve production efficiency. Companies can implement procurement strategies for pipes and valves to prevent dirty prints in the primary process, ensuring smooth material supply and minimizing disruptions. Although actual production plan achievement hasn't reached 100%, this strategy has the potential to increase product sales by 3.31% by reducing the rejection ratio of dirty prints. Ultimately, proactive procurement of spare pipes and valves is expected to increase production efficiency by 4%, indicating enhanced production schedule stability.
The Measurement of Job Stress Levels on Study Concentration in Students Who Study While Working (Case Study: Gunadarma University Postgraduate Students)
The concentration of studies is very important to support students in understanding the theory and understanding the concepts during learning activities so this needs to be noted so that students can achieve good learning outcomes. Studying while working will certainly cause serious problems to the process of activities on campus and at work. Problems that often occur are piling up tasks, difficulty managing time, fatigue, disputes between colleagues and superiors, a toxic work environment, limited rest time, being expelled from university, and experiencing a delay in graduation. These can trigger job stress for students because they have to do two activities in their daily lives. This study aims to find out the effect of job stress levels on study concentration in working students. In addition, this study analyzes the factors that influence job stress and study concentration. The method used is quantitative analysis with a non-probability sampling technique with a purposive sampling technique. The analysis of data carried out was a Chi-Square test and t-test. Based on the results shows that students who study while working have a very high level of job stress which causes a decrease in learning concentration in students. In addition, several factors influence job stress and study concentration, namely gender, age, type of work, and length of work duration. This research contributes to providing an overview and consideration to students about students who study while working.
Analysis of Safety Climate Factors to Improve Occupational Safety and Health in Construction Work at PT XYZ Bunyu Field
The industry of oil and gas is a something complex, there are many potential hazards and risks that cause quite high work accidents, for example, the dangers of toxic gases, explosion hazards, fire hazards, electrical hazards, moving equipment hazards, and gravity hazards caused by lifting operations. Based on the observations in the field, many jobs were found to be stopped because to finding related to unsafe actions and unsafe conditions in the location that could be exposed to equipment and workers, so that they could cause material losses and fatalities. Action that can be taken to improve the occupational health and safety are by making a good safety climate in the work location. The research is to improve the occupational health and safety provide the improvement solutions based on safety climate factors that the most role in improving occupational health and safety in construction work activity. Explpratory Factor Analysis used to describe data structure and interconnected structure analyze in a number of variables by making a factor. The factor analysis results show a total variance of 86.538%. The most dominant factor in the safety climate regarding occupational health and safety in construction work is the training and compliance factor, while the factor that is not dominant is the occupational health and safety promotion factor which is based on the magnitude of the eigenvalue.
The Effect of Employee Engagement on Employee Performance by Moderation of Generational Characteristics of Employees in Private Agencies
Employee engagement is an important issue that is the main concern of the organization's leaders in managing its employees. The changing characteristics of the employee generation are becoming a specific challenge for human resource management. Employees who are engaged with their work will exert all their abilities, efforts, and thoughts and significantly contribute, where the engagement and personal characteristics possessed by employees in carrying out their work can directly impact their performance. This study aimed to analyze employee engagement's effect on employee performance by moderating the generational characteristics of private agency employees in the City of Padang, West Sumatra. Data was collected through questionnaires distributed to 100 employee respondents working in private institutions in the city of Padang, with purposive sampling technique. Then, the data is processed using the Partial Least Square-Structural Equation Modeling (PLS-SEM) method. The results of this study indicate that employee engagement generational characteristics (Y and Z generation) have a positive and significant effect on employee performance. Generational characteristics (Y and Z generation) also positively and significantly impact employee engagement. Generational characteristics do not moderate the relationship between employee involvement and employee performance, but directly employee engagement and employee performance can be improved with generational characteristic variables. Organizational leaders should pay attention to employee engagement and the characteristics of the generation of employees and can make it a potential to improve employee performance.
A New Approach to Designing Blood Supply Chain Risk Mitigation
Blood is an essential component for body and plays critical role in human survival. Hospital blood banks (HBB) are responsible for ensuring availability and safety of blood in particular area. Risks that could arise in blood supply chain at HBB need to receive full attention, especially in the event of an outbreak or disaster. This attention is necessary to ensure smooth flow of activities, information, products, and finances. The primary objective of this research is to develop risk mitigation design for the blood supply chain. This research focuses on case study at HBB in Bandung City with specific focus on packaged red blood cells. The new approach used in this research involves initiating process by collecting potential risks, which are then defined and classified within the supply chain operations reference (SCOR) model. Subsequently, questionnaires were distributed to gather input for calculating weights using the analytical hierarchy process (AHP). Following step involves identifying root cause of these risk through fault tree analysis (FTA) and determining the most influential risk causes using failure mode effect and analysis (FMEA). Final phase entails designing strategies for mitigating risks in blood supply chain. This research aims to assist HBB facilities in prioritizing risks for treatment and implementing strategies to minimize these risks within their respective areas. According to AHP results, risk with the highest weight (0.173) is unavailability of blood stock at Indonesian Red Cross due to a shortage of donors. This risk can be mitigated by incorporating blood donation activities in agencies and HBB. The new approach in the research could provide more detailed mapping of blood supply chain risks.
Comparison of Moving Average and Exponential Smoothing Methods for Estimating the Number of Internet Service Disruptions
Fairly tight competition in telecommunication business requires companies to continue improving the quality of their services, including handling network problems or customer complaints. However, the amount of disturbance that occurs is often unpredictable. Indeed, this condition will impact the allocation of resources and budget for handling customer disturbances in the following period, with uncertainty. This research aims to apply the moving average (MA) and single exponential smoothing (SES) forecasting methods to predict the number of internet service disruptions. The case study used in this paper is an internet service provider company with service coverage in the northern part of Surabaya. The number of disturbances data was collected from January 2022 to May 2022, with 18,453 data in total. The disturbances can be divided into five types: physical, mass, logical, PSB/migration, and others. Forecasting is carried out using the MA method with a period of three months. Meanwhile, forecasting using the SES method was carried out by first determining the alpha value that produces the smallest Mean Absolute Percentage Error (MAPE) value. The analysis results show that both forecasting methods are relatively effective and efficient in estimating the number of disturbances. Forecasting performance testing was carried out by measuring the Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) values. The results of forecasting performance measurements show that the SES method is much better than MA for all types of disturbance data, with MAPE values ​​below 2%.
Rough Cut Capacity Planning Using a Skill Matrix for Fulfilling Orders at PT X Furniture Manufacturing
The COVID-19 pandemic has had a significant impact on a variety of sectors, including the furniture manufacturing industry. The industry is undergoing drastic demand changes, complicating adjustment efforts during the pandemic. Additional human resources (HRM) is becoming a more complex challenge due to strict health protocols and the necessary vaccination efforts. In this context, increased availability of capacity has become critical, but an appropriate approach has not been revealed in the literature. As for the in-depth literature study, it covers various methods of increasing production capacity, such as adding human resources, machines, shift work systems, overtime, and subcontractors. The research focuses on a new way to multi-skill by using the skill matrix as an innovative method to increase the availability of capacity at PT X, a furniture manufacturing company. Using Rough Cut Capacity Planning (RCCP), the study describes current production capacity, analyzes the impact of post-COVID demand shifts, and evaluates the effectiveness of multi-skill application with a skill matrix in improving production flexibility and responsiveness. The research findings provide valuable insights for furniture companies and related sectors in dealing with post-COVID dynamics, as well as providing the basis for developing more adaptive and sustainable capacity planning strategies.
Analysis of the Influence of E-Service Quality, E-Word of Mouth, and Promotion and Ads on Consumer Loyalty in the Marketplace
The trend of digital-based transactions continues to increase along with the implementation of social restrictions during the pandemic, even it becomes a new habit for the millennial generation after the pandemic ends. In Southeast Asia, Indonesia was the first rank for the retail sales through e-commerce in 2021. The competition among e-commerce, especially the marketplaces in Indonesia has become very tight. Customer satisfaction, trust and loyalty are the important indicators for improving marketplace performance. In this research, there are three main factors that are further investigated for their influence on customer satisfaction, trust, and loyalty namely e-service quality, e-word of mouth along with promotion and ads. The research was conducted on 162 Tokopedia user with the majority of the millennial generation. Hypothesis testing was carried out using the partial least square structural equation (PLS-SEM) technique. The results of this study indicate that e-service quality has a significant effect on loyalty through satisfaction and trust, promotion and ads has a significant effect on loyalty through satisfaction, and e-word of mouth has no significant effect on satisfaction, trust and consumer loyalty. To get consumer loyalty, the marketplace can improve e-service quality which has the most significant effect followed by promotion and ads.
Analysis of Operators' Mental Workload Using the NASA-TLX Method at PT XYZ
PT XYZ is a fermentation industry that uses Human Machine Interfaces (HMI) in the production process. With high mental workload of operators, it can disrupt company productivity. In 2021, the achievement of the percentage of production failure targets at PT XYZ has not reached the set target. The purpose of this study is to measure and make improvements to the mental workload at PT XYZ. The research method is to measure mental workload using the NASA TLX questionnaire, conduct data analysis using descriptive statistics, and conduct a paired t-test to compare the results of mental workload before and after improvement.. From the research results, the mental workload score was 72.64 in the high category. Of the six NASA TLX dimensions, operators experienced time demands of 24.1%, effort 23.1%, mental demands 22.3%, performance 20.2%, physical demands 9.3% and frustration 1.0%. The improvement results can reduce the high mental workload of operator from 82 to 74 with a significant level of 0.004, and increase the low mental workload of operators from 53 to 66 with a significant level of 0.129.
Integrating Sustainable Development Principles in Learning Mathematics to Stimulate Sustainable Skills in Future Generations
This research constitutes a literature review employing a qualitative approach, analyzing scholarly articles, books, and other documents related to sustainable development. This article aims to summarize and analyze previous studies concerning sustainable development in the context of mathematics education, as well as strategies that can be employed to integrate the principles of sustainable education. Integrating the principles of sustainable development into education, including mathematics education, is crucial in fostering a more environmentally responsible society and promoting sustainability across all sectors. However, its implementation remains limited. Educators face various challenges, including a lack of time, resources, and understanding of sustainable education, along with a dearth of supportive teaching materials. The principles of sustainable development can serve as a framework for developing curricula and teaching practices that are more sustainable. Educators can select mathematical problems related to environmental or social issues, discuss relevant mathematical concepts in connection with these problems, and help students comprehend the impact of mathematical decisions on the environment and society. Integrating the principles of sustainable development into mathematics education not only aids in producing a generation with sustainable skills but also motivates students to learn mathematics in more engaging and meaningful ways. A learning approach centered around sustainable development can be an effective way to prepare students for a sustainable future. The article also underscores the necessity for curriculum development, training, and professional advancement for educators.
Actors' Behaviours in Responding to Green Incentives in the Food and Beverage Industry: A Scoping Review
Understanding the actors' behavior is an essential step to recognizing the standpoint of each actor to generate a strategy that facilitates collaboration and healthy coopetition in creating a green and sustainable impact. By defining a suitable strategy, the optimization of collaboration and coopetition in a sustainable food and beverage supply chain can be performed through game theory optimization. Therefore, this study aims to understand the description of the actors' behaviors corresponding to sustainable incentives in the food and beverage industry in existing game-theory optimization literature. This study was carried out by conducting a literature scoping of two significant databases: Scopus and Web of Science. 1816 articles were identified in the initial selection, and 25 were deeply evaluated and mapped. The literature scoping review shows that the supply chain's performance and interaction are related to the actors' actions, which have an independent interest, though they share a common desire to maximize its benefits. The main financial incentives are found in the game theory literature. However, the other incentives are not yet explored thoroughly. In the near future, it is suggested to conduct research on formulation of ethical and social incentives in order to be utilized in game theory optimization.