Jurnal Rekayasa Sistem Industri

The Measurement of Job Stress Levels on Study Concentration in Students Who Study While Working (Case Study: Gunadarma University Postgraduate Students)

2024-05-14T10:49:36+07:00

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.

Pengaruh Aksesibilitas, Konektivitas, Kualitas Pelayanan, dan Kepuasan Penumpang Terhadap Loyalitas Penumpang Mass Rapid Transit (MRT) Jakarta

2023-08-28T09:13:56+07:00

Traffic congestion is one of the main problems faced by people in Jakarta. In fact, the government has already provided various public transportation services to overcome the traffic congestion. However, it seems that people, especially in Jakarta, prefer to travel using their private vehicles. The accumulation of private vehicles is one factor contributing to the traffic congestion in Jakarta, which is difficult to overcome. Therefore, it is necessary to examine what factors can influence passenger’s loyalty to using public transportation, in this case, the MRT Jakarta. In this research, the direct and indirect effects of accessibility, connectivity, and service quality factors will be tested on passenger loyalty through the passenger satisfaction factors. The sampling method used in this research is purposive sampling with the inverse square root method to determine the minimum sample. The data will be processed by using Partial Least Squares Structural Equation Modeling (PLS-SEM) method with the help of SmartPLS software. As a result, it was found that the factors that directly influence passenger satisfaction are accessibility, connectivity, and quality of service. The factors that directly affect passenger loyalty are connectivity and passenger satisfaction. Lastly, the two factors that indirectly affect passenger loyalty through satisfaction are accessibility and service quality. From the results of this study, it is suggested that the MRT Jakarta management can improve MRT connectivity by shortening the waiting time between station stops, providing clarity regarding information for the next stop, clarity of information for passengers to make transfers with other modes of transportation, and convenience in transferring using other modes of transportation. With improved connectivity, accessibility, and quality of MRT services, passenger loyalty is hoped to increase.

Usulan Perencanaan Persediaan Produk FMCG Menggunakan Metode Algoritma Apriori dan Jaringan Syaraf Tiruan (JST) pada PT Borwita Indah

2023-10-04T13:12:38+07:00

The problem faced by PT Borwita Indah is the occurrence of overstock and understock on FMCG products. This study aims to determine the inventory planning of FMCG products with related factors, namely sales results, stock of finished goods, and to be able to predict accurately so that there is no buildup of products in the warehouse. This research using the apriori algorithm for data collection with associative rules which is carried out through support and confidence calculation mechanisms and artificial neural networks for forecasting methods which have a fairly low data error rate and are good enough in the generalization process so that this model is able to predict timeseries data for several time periods for future. Itemset data pattern obtained resulted in a level of confidence in Head&Shoulders with Pantene 90.9%, and a level of confidence in Pantene with Head&Shoulders 90.9%. Meanwhile, the level of confidence for Vicks with Head&Shoulders reaches 100%. Forecasting results for the next 12 periods for each Pantene, Head&Shoulders, and Vicks product have a fluctuating forecasting trend so that safety stock can be taken into account. The amount of safety stock that must be in the company is 504 pcs of Pantene per day, 49 pcs of Head&Shoulders per day, 35 pcs of Vicks. It is hoped that with this research the company can carry out optimal product inventory control.

Analysis of Operators' Mental Workload Using the NASA-TLX Method at PT XYZ

2023-11-29T12:47:41+07:00

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.

Combining the Servqual and Kano Models to Find Out How Satisfied Customers are with Swab and PCR Services

2023-10-09T06:38:11+07:00

Swabs and PCR are ways to track patients infected with COVID-19. One private swab and PCR service provider in Surabaya offers swab and PCR tests with fast results and is open 24 hours a day. This research aims to determine service quality performance, identify the causes of consumer dissatisfaction, and identify service attributes that must be maintained and improved for Swab and PCR services in Surabaya. This research uses an integration of the Servqual and Kano methods. The integration of Servqual and Kano determines the service attributes to be improved. Data was obtained from a questionnaire using the five-dimensional Servqual approach, then calculated to get a gap value and categorized using the Blauth formula. The Servqual gap and the Blauth formula's category values are combined to make action decisions. The results state that swab and PCR service providers still need to improve all factors used in this research. Three attributes fall into the weak and indifferent category, so the decision that needs to be made is to ignore them because they do not affect consumer satisfaction and are not a priority for improvement. The other twenty-one attributes fall into the weak and one-dimensional category, meaning companies must improve these attributes to satisfy consumers. Companies need to make improvements to ensure better service, including increasing the number of medical officers to reduce fatigue and queues and providing training on medical procedures and communication skills for medical officers.

Efficiency Tax Reporting System as Variable Moderation for Digitalization of Tax Compliance

2023-11-03T07:46:52+07:00

The goal of this research is to examine the impact of tax digitalization, such as e-filling, and e-billing, on the efficiency of individual taxpayer reporting and tax compliance in the 4.0 era. The presence of tax digitalization as a type of tax administration modernization makes it easier for the general public, particularly taxpayers, to carry out their obligation. This study is a quantitative research. This study's variables include one dependent variable, two independent variables and one variabel moderating. The dependent variable is the tax compliance, while the independent variables are the use e-filling, and e-billing and the moderating variables is efficiency of taxpayer reporting. The population in this study is Individual taxpayers in Kuningan Regency, West Java. The samples in this research are 50 respondents that take the questionnaire with Likert scale as the measurement. This study used incidental sampling, with the research instrument being an online questionnaire distributed via social media. The data analysis method in this study uses Moderated Regression Analysis (MRA). According to the findings of this study efficiency tax system has not been proven to moderate the relationship between e-filling and e-billing with the tax compliance.

The Effect of Employee Engagement on Employee Performance by Moderation of Generational Characteristics of Employees in Private Agencies

2024-04-01T08:56:55+07:00

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.

Analysis of Mental Workload in Appropriate Technology (AT) for Agricultural Machinery Using Heart Rate Variability (HRV) Parameters

2023-10-26T08:36:54+07:00

Appropriate Technology (AT) is designed to substitute manual work and to increase productivity for small-medium businesses. Due to its low-cost technology that affects its design quality, the acceptance of AT appears to be low. A guideline has yet to be available to determine AT's design quality. The purpose of this study was to explore the efficacy of physiological measures collected from a Heart Rate Monitor (HRM) in differentiating mental workload in using AT. If applicable, these measures can provide objective data for AT evaluation. Several parameters were collected from HRM, including frequency domain and time domain. Two ATs were used for evaluation that represented “good” and “poor” agricultural processing machines. Eleven participants were involved in this study in which they used both ATs. The result of this studyis the ratio of Low Frequency and High Frequency (LF/HF) parameter detects differences perceived by the participants. The increase in the LF/HF value from the Commercial Extruder to the Customized Extruder is directly proportional to the increase in mental workload, where the Commercial Extruder is defined as a “good” AT design, and the Customized Extruder as a “poor” AT design. Therefore, it can be concluded that designs with specific guidelines can reduce the mental workload perceived by operators.

Introducing Copula Functions to Estimate the Reliability of Dependent Mechanical Systems

2023-11-09T09:07:37+07:00

This paper addresses the challenge of assessing the reliability of complex mechanical systems where components are inherently correlated in their failure modes. Traditionally, the assumption of independence among these components has been employed, but it often fails to capture the real-world complexities. To overcome this limitation, copula functions are introduced as a robust methodology for modeling the dependent relationships between correlated variables within mechanical systems. This paper aims to demonstrate the utility of copulas in estimating system reliability while accounting for these dependencies. The results reveal that the Clayton copula emerges as the most suitable model for representing dependence in such systems. Importantly, the reliability estimates obtained through copula-based methods not only reflect the complex interdependencies accurately but also align with the principles of the boundary theory of reliability. This research underscores the potential of copula-based reliability estimation as a valuable alternative, offering a more comprehensive and precise assessment of reliability in complex mechanical systems and holding significant promise for practical engineering applications. This framework allows the consideration of dependence among the observed variables that is usually overlooked in engineering practice.

Determining the Profiles of Local and Tourist Visitors to Determine Retail Strategies

2023-11-24T14:37:18+07:00

The tourism sector undeniably has a significant economic impact on a region. One of the activities of tourists is shopping, which can create an additional market share for retailers. Therefore, retailers need to seize this opportunity by implementing strategies tailored to the profiles of both local and tourist visitors. This article proposes a retail strategy based on the analysis of local and tourist visitor profiles, using transaction data from Point of Sales (POS) to classify visitors based on their distance from the retailer. Hypothesis testing is conducted to understand the differences in purchasing patterns between local and tourist visitors, along with K-means clustering techniques to group visitors based on distance, age, and purchase value. The interpretation of clustering results helps identify purchasing patterns in each group, enabling retailers to adjust marketing and promotional strategies according to customer profiles. Through clustering analysis in a case study of a retailer in Yogyakarta, Indonesia, three main customer groups were identified: inactive, active, and out-of-town visitors. Retailers should prioritize efforts on active groups, especially Cluster 4, with active members and high transaction values. Clusters 6 and 9 should also be targeted to increase the probability of becoming Cluster 4. Group 1 can be disregarded in marketing efforts, and retailers should tailor their strategies for Group 3 based on their visitation patterns.

Analysis of the Influence of E-Service Quality, E-Word of Mouth, and Promotion and Ads on Consumer Loyalty in the Marketplace

2023-12-19T16:59:48+07:00

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.

A New Approach to Designing Blood Supply Chain Risk Mitigation

2024-04-01T08:38:09+07:00

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

2024-03-01T13:56:23+07:00

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

2024-02-09T09:15:10+07:00

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.

Application of the Lightning Search Algorithm with 2-Opt Local Search for Solving the Asymmetric Traveling Salesman Problem

2024-06-02T10:47:43+07:00

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.