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This study aims to analyze the impact of Brand Ambassador, Website Quality, and Product Variety on Purchase Decisions in Shopee E-Commerce in Jakarta. The data used in this study is primary data obtained through the distribution of questionnaires to Shopee users in Jakarta. The sampling technique used is Non-Probability Sampling, with the method being Accidental Sampling. The sample size taken was 103 respondents based on the Lemeshow formula. This study focuses on three key variables that are believed to have a significant impact on consumer purchase decisions. Brand Ambassador refers to public figures or celebrities who represent a particular brand and can influence consumers' perceptions of the products offered. The role of a Brand Ambassador is crucial because it can enhance the attractiveness and credibility of a product in the eyes of consumers. Website Quality includes aspects such as design, navigation, loading speed, and user-friendliness while shopping. A website that is easy to use, fast, and visually appealing will enhance user satisfaction, which in turn can encourage purchasing decisions. Product Variety is related to the range of products available on the e-commerce platform, offering consumers more choices to meet their needs. The more varied the products offered, the higher the likelihood that consumers will make a purchase. The analysis tool used in this study is SPSS version 26 for regression analysis. The research findings show that Brand Ambassador, Website Quality, and Product Variety have a significant effect on Purchase Decisions in Shopee E-Commerce in Jakarta. An attractive Brand Ambassador, a high-quality website, and a wide variety of products have been proven to influence consumers’ purchase decisions. These findings indicate that Shopee E-Commerce needs to continuously improve these factors to enhance consumer experience, strengthen loyalty, and increase sales.

The loading in and loading out processes are crucial stages in event production. Although often invisible to the audience, they have a direct impact on the smooth running and quality of the event. This study aims to examine the implementation of the loading process at the Pancaverse event held at Depok City Square, focusing on technical dynamics, field challenges, and the implemented solution strategies. This study uses a descriptive qualitative approach through a case study, where data was obtained through field observations, in-depth interviews with five key informants, and technical documentation of the event. The results show that the success of the loading process is highly dependent on several key factors, including detailed planning, clear work zone division, and responsive inter-team communication. Thorough planning before the event begins is crucial to minimize technical errors during the loading process. Furthermore, a structured work zone division facilitates coordination between teams and accelerates workflow. Effective communication between teams, both internally and with external parties, also significantly influences the smooth running of the loading process. However, external factors such as bad weather and miscommunication between vendors are major challenges faced. These challenges can impact the smooth logistics and the overall loading process. Therefore, risk mitigation is carried out through cross-checking logistics, intensive coordination with external parties, and providing backup plans in case of obstacles. The use of a logistics checklist and tagging system has also proven effective in accelerating the identification of goods during unloading, thereby streamlining the loading and unloading process. Overall, this study emphasizes the importance of technical and managerial readiness in handling the loading process as an integral part of event production. These findings are expected to provide practical insights for event industry players in designing and implementing more adaptive and efficient logistics strategies in the field.

The Cargo oil pump is one of the auxiliary units on board a ship, used to transfer cargo from one location to another during loading and unloading operations. On the MT Pangrango vessel, an issue occurred with the cargo oil pump: its performance declined, resulting in slow suction during the unloading process. This problem hindered efficient cargo operations, as the pump was not functioning properly.This study aims to identify the contributing factors, impacts, and countermeasures for the decreased performance of the cargo oil pump. The research methodology applied in this thesis involved a descriptive approach combined with Miles and Huberman’s analytical method, with data validity tested via triangulation. Data collection techniques used to identify the problem included observation, interviews, documentation, and literature review.The results revealed that the pump’s shaft was worn due to excessive friction, and the ball bearing s exhibited wear and disintegration caused by lack of lubrication (grease). The recommended corrective actions were to add material to the shaft , perform realignment to correct any shaft misalignment, and implement routine maintenance—specifically, monthly grease lubrication. These measures, when properly applied, can significantly reduce the risk of Cargo oil pump damage.

To support the smooth operation of maritime transportation, particularly in the transportation of liquids such as FAME oil, factors that can influence cargo loss must be properly managed. Deterioration in quality or loss of cargo volume can occur for several technical and non-technical reasons. One of the main factors causing FAME cargo loss is a leak in the ship's hull or poorly maintained tank structures, resulting in partial cargo loss during the voyage. Furthermore, inappropriate vessel characteristics, such as suboptimal carrying capacity, are also a major cause of cargo loss. Inaccurate unloading and unloading procedures, such as careless handling, also contribute to this problem. The impact of FAME cargo loss is significant, both financially and on the company's reputation. Claims received from charterers regarding losses can be detrimental to the company, and decreased customer confidence can impact shipping volumes and revenue. To minimize the risk of cargo loss, companies need to implement effective strategies, such as routinely inspecting vessels and storage tanks to ensure there are no leaks. Training crews in proper loading and unloading procedures is also crucial to avoid human error that can lead to losses. Implementing a regular visual and technical inspection system will improve operational quality and minimize cargo loss during FAME transportation. Furthermore, the use of more advanced monitoring technology, such as sensors to detect leaks or changes in tank pressure, can help detect problems early. Data-driven maintenance management systems can also be used to monitor vessel condition and optimize maintenance schedules, thereby reducing the risk of damage that could lead to cargo loss.

Fatigue is a critical issue in labour-intensive small industries, especially in traditional food production such as tofu manufacturing. This study aims to develop a fatigue classification model using a decision tree algorithm by integrating subjective assessments of the work system through the Macroergonomic Organizational Questionnaire Survey (MOQS) and objective physiological indicators, specifically Cardiovascular Load (CVL). The research was conducted in a tofu home industry located in Kalisari Village, Banyumas, Indonesia. Primary data were collected from 10 workers through MOQS questionnaires and heart rate measurements taken at rest and during work. CVL values were calculated and used as labels for classification into three categories: low, moderate, and high fatigue. Meanwhile, MOQS dimension scores (organization, job, personal, environment, and technology) were transformed into interval data and used as classification features. A decision tree model was built using the CART algorithm and visualized for interpretability. The results show that all workers experienced at least moderate fatigue, with 20% categorized as high fatigue. The decision tree revealed that the dimensions of organizational and personal factors were the most influential in predicting fatigue levels. The model provides a practical and interpretable tool to support decision-making in scheduling, workload balancing, and ergonomic interventions. This study demonstrates a novel approach to combining macroergonomic assessments and physiological data with machine learning for practical fatigue risk management in small-scale food production environments.

This study aims to analyze the effect of price on purchasing decisions with consumer satisfaction as a mediating variable on Nestlé Pure Life drinking water products. The type of research used in this study uses a quantitative study by distributing questionnaires via google form which are distributed online.  The sample in this study were consumers who had bought nestle pure life drinking water in the Yogyakarta area. The number of samples used in this study were 100 respondents. The analysis technique used in this study uses the SmartPls version 3 program with Convergent Validity, Factor Loading, Average Variane Extraked (AVE), Discriminant Validity, Fornel Larcker, Cross Loading, Reliability, Cronbach Alpha, Composite Reliability, R Square, and Hypothesis Testing tests. The results of this study indicate that price has a significant effect on customer satisfaction, price has a significant effect on purchasing decisions, customer satisfaction has a significant effect on purchasing decisions and the effect of price on purchasing decisions mediated by customer satisfaction.

This study rigorously investigates the Ulul Albab spiritual leadership construct and its impact on psychological well-being among campus da'wah activists, employing a Confirmatory Factor Analysis (CFA) approach grounded in both theoretical integration and empirical data. The inquiry draws upon a meta-analysis of 47 quantitative studies encompassing a total of 12,847 respondents from leading universities in Indonesia, Malaysia, and Brunei Darussalam, spanning the years 2018 to 2024. This methodological scope enhances the external validity of the findings. The CFA results confirm that the Ulul Albab spiritual leadership model exhibits a robust level of model fit, as indicated by optimal statistical indices (χ²/df = 2.34; CFI = 0.956; TLI = 0.943; RMSEA = 0.047; SRMR = 0.039), suggesting strong coherence between the theoretical construct and field data. The three core dimensions conceptualized in this model are statistically validated through high factor loadings: intellectual spirituality (0.847), Islamic transformational leadership (0.823), and emotional-spiritual intelligence (0.791), each serving as integral pillars of the Ulul Albab paradigm. Furthermore, structural regression analysis reveals a significant effect of Ulul Albab spiritual leadership on the psychological well-being of da'wah activists (β = 0.673; p < 0.001; R² = 0.453), thereby affirming the model's predictive strength in fostering individual potential rooted in Islamic spiritual values. These findings reinforce the theoretical propositions advanced by Garden, M. (2004), Fry (2003), and Zohar and Marshall (2000) regarding the significance of spiritual leadership within organizational dynamics. However, this study offers a novel conceptual contribution through the epistemological synthesis of the Ulul Albab construct, integrating intellectual and spiritual intelligence within a holistic Islamic framework. Unlike Western-based models of spiritual leadership proposed by Fry and Nisiewicz (2020), the Ulul Albab construct demonstrates a notable advantage in the dimension of intellectual spirituality, as evidenced by its higher factor loading (0.847 compared to 0.634), underscoring the imperative of balancing dzikir and fikir as both ethical and cognitive foundations in contemporary Islamic leadership.

This study aims to analyze the effect of leadership style and compensation on employee performance with work motivation as an intervening variable at Pamella Tiga Yogyakarta. The population and sample in this study were Pamela Tiga Yogyakarta employees totaling 45 respondents. This research uses a quantitative approach with survey method and data analysis using SmartPLS with Concurrent Validity test, Loading Factor, Average Variane Extracked (AVE), Discriminant Validity, Fornel Larcker, Cross Loading, Reliability, Cronbach Alpha, Composite Reliability, R Square and Hypothesis Testing. The results showed that there was no positive and significant effect of Leadership Style (X1) on employee performance (Y) at Pamella Tiga Yogyakarta, there was a positive and significant effect of Compensation (X2) on employee performance (Y) at Pamella Tiga Yogyakarta, there was a positive and significant effect of Leadership Style (X1) on Work Motivation (Z) at Pamella Tiga Yogyakarta, There is a positive and significant effect of Compensation (X2) on Work Motivation (Z) at Pamella Tiga Yogyakarta, There is a positive and significant effect of Work Motivation (Z) on employee performance (Y) at Pamella Tiga Yogyakarta, There is no positive and significant effect of Leadership Style (X1) on employee performance (Y) mediated by Work Motivation (Z) at Pamella Tiga Yogyakarta, There is no positive and significant effect of Compensation (X2) on employee performance (Y) mediated by Work Motivation (Z) at Pamella Tiga Yogyakarta.

The purpose of this study is to examine how Super Dazzle Gejayan's pay and work environment affect staff performance, using job satisfaction as a mediating variable. Quantitative research is the research methodology employed. The 142 employees of Super Dazzle Gejayan made up the study's population. Partial Least Square (PLS) with Convergent Validity, Factor Loading, Cronbach Alpha Discriminant Validity, Cross Loading, Reliability, Composite Reliability, R Square, and Hypothesis Testing tests were used to analyse the study's sample of 60 respondents. According to the study's findings, pay has no bearing on worker performance, while work environment has a positive and significant impact on worker performance. Job satisfaction also has a positive and significant impact on worker performance, and compensation has a positive and significant impact on worker satisfaction. Job satisfaction also acts as a mediating variable in the relationship between work environment and worker performance.

Engine overheating is a critical condition that can cause damage to internal components, reduce operational efficiency, and lead to overall system failure. The absence of an automatic protection system is one of the primary factors contributing to damage. This study aims to design and test a temperature sensor-based safety device that can automatically cut off the engine's working system when the temperature exceeds the safe limit. The method used is descriptive statistical analysis to evaluate the effect of independent variables (operational time duration and workload) on the dependent variable (coolant temperature). The system was tested through water heating simulation using an electric heater and controlled by an Arduino Nano microcontroller, a MAX6675 temperature sensor. Testing was carried out with variations in power load (150, 300, 450, 600, and 750 Watts) and operational duration (20, 40, and 60 minutes). Temperature data were collected and analyzed using ANOVA to determine the effect of load and time on temperature increase. The results showed that the temperature increased significantly with increasing power load, with temperatures approaching 100°C at loads ≥450 Watts in less than 20 minutes. The load variable shows a significant effect on temperature (p < 0.05), while the duration of time shows a nonlinear but not statistically significant upward trend. The safety device is proven to be able to automatically disconnect the system when the temperature reaches the specified maximum limit, thus effectively preventing engine damage due to overheating.

This paper is to determine the Role of PBM Wahana Intradermaga Niaga in the Dry Bulk Unloading Process at PT. Pelabuhan Belawan. Unloading activities are activities to unload goods from the ship's hold to the dock in the ship's hull or vice versa (stevedoring), activities to move goods from the dock using a conveyor to the warehouse/stacking yard or vice versa (cargodoring) and activities to pick up goods from the warehouse/yard carried onto a truck or vice versa (receiving/delivery). A dry bulk carrier is a ship specifically designed to be able to transport various dry bulk loads. In the distribution of dry bulk cargo there is an unloading process. Unloading aims to lower and raise goods from the ship to the port or vice versa. And in supporting this goal requires unloading equipment. The unloading equipment in question comes from the port. In carrying out the unloading process, MV. S Grace has obstacles in carrying out unloading. So that the purpose of unloading is not achieved optimally. Therefore, an analysis is needed to determine the factors that inhibit the productivity of dry bulk unloading so that unloading activities can run optimally. From the results of reading and observing this paper, the author states that the implementation of unloading has inhibiting factors, namely external factors. Crane breakdown and bad weather are inhibiting factors in the dry bulk unloading process. Based on these factors, it has an impact on unloading delays that are not according to schedule and increase ship queues. Therefore, the author suggests that port operators or ship crews carry out routine maintenance on the equipment used for loading and unloading so that dry bulk loading and unloading can run optimally. This paper uses the field research method and the library research method (data collection from the library).  

During this process of monitoring the contents (volume) of the patient's urinary catheter manually, the nurse must go around one by one to the patient's inpatient room to ensure the contents (volume) of the patient's urinary catheter. This process takes quite a long time while patients who use urinary catheters at the hospital are not small. In addition, if the patient's urinary catheter monitoring process is still done manually, sometimes the medical team or nurses often miss or forget, that the urine bag (catheter) is full. The purpose of this study is to design an Internet Of Things Based Urine Bag Monitoring. The research method used in this study was experimental. The population in this study was 65 TREM study program students with a sample of 40 respondents. Based on the average score table of the Simplicity, Interactivity and Usability surveys. The results of the score calculation using the Likert scale from the Simplicity, Interactivity and Usability factors of urine bag monitoring testing that has been carried out using questionnaires to respondents have shown a high score that is almost close to the value of 5 based on calculations carried out using the Likert scale which indicates that this urine bag monitoring tool can be well received by respondents. It is expected to be developed as material for further research related to monitoring urine bags using applications that can usealarms on users' smartphones and can also use batteries on urine bag monitoring tools

This research was conducted at PTPN IV Regional II Adolina Palm Oil Plantation and Mill Unit with the aim of evaluating the effect of Ripple Mill machine efficiency on palm kernel impurity levels through a multiple linear regression analysis approach. Ripple Mill is a vital piece of equipment in the palm kernel cracking process, which plays a role in determining the quality of the palm kernel. This machine works by breaking the kernels to produce kernels that are separated from the shells. However, when machine efficiency decreases due to technical and operational factors, palm kernel impurity levels tend to increase, characterized by an increase in shell fragments, fibers, and other foreign materials. This condition can have an impact on decreasing product quality and increasing further processing costs. Data collection was carried out over five days of observations covering the variables of machine efficiency and kernel impurity levels obtained from production results. The study found a strong negative correlation between machine efficiency and impurity levels in palm kernels. This means that the higher the efficiency of the Ripple Mill, the lower the resulting palm kernel impurity levels. This finding also confirms that quality control in the production process is not only determined by raw material factors but also highly dependent on the performance of the processing machine. Furthermore, the research results demonstrate the importance of implementing preventive maintenance strategies, including regular inspections of the rotor bar, square bar, and drive motor, as well as regulating operating parameters such as rotational speed and machine load. Proper preventive maintenance and operational control are essential to sustain machine efficiency and product quality. Therefore, continuous improvement in technical and managerial aspects is essential to maintain palm kernel quality and support optimal palm oil mill productivity.

This study is motivated by the low utilization rate of the National Digital Samsat (SIGNAL) application in Padang City, which only reached 2.1%. According to Grajek and Kretschmer (2008), a digital technology can be considered to have reached the critical mass phase when adoption rates range between 10% and 25% of the target market (Mahler & Rogers, 1999; Cool et al., 1995). Therefore, the adoption level of SIGNAL in Padang is still considered very low and has not yet entered a self-sustaining phase. This study aims to analyze the factors that influence the acceptance of the SIGNAL application using the Technology Acceptance Model (TAM). A quantitative method was applied, using data from 99 respondents analyzed through PLS-SEM with SmartPLS 4.0. The results show that Perceived Ease of Use (PEU) significantly affects both Perceived Usefulness (PU) and Attitude Toward Using (ATU), while PU does not significantly influence ATU. PU and ATU have a significant influence on Intention to Use (ITU), which subsequently affects Actual System Usage (USE). The strongest outer loading indicators were: “easy to understand” (0.854) for PEU, “improves productivity” (0.803) for PU, “rejecting alternative options” (0.861) for ATU, “motivation to continue using” (0.852) for ITU, and “user satisfaction” (0.856) for USE.

Kota Padang merupakan salah satu kota yang ada di Provinsi Sumatera Barat dan juga merupakan ibu kota dari Provinsi Sumatera Barat yang saat ini memiliki perkembangan di berbagai bidang seperti bidang ekonomi, transportasi dan perkembangan infrastruktur kota itu sendiri. Akibat perkembangan penduduk dan transportasi maka akan membutuhkan angkutan umum sebagai penunjang perkembangan tersebut. Tujuan dari pelaksanaan penelitian ini adalah untuk mendapatkan data kinerja pelayanan angkutan sebagai bahan evaluasi dalam penataan angkutan umum di Kota Padang. Hasil dari penelitian ini yaitu Frekuensi tertinggi terdapat pada trayek 419 yaitu 39 Kend/jam sedangkan frekuensi terendah adalah sebesar 1 kend/jam yaitu pada trayek 404, 411, 412, 423, 444,445, 410A, dan 444B. Headway tertinggi yaitu pada trayek 404 dengan headway 596 menit, sedangkan headway terendah terdapat pada trayek 419 dengan headway 2 menit.Load factor tertinggi terdapat pada trayek 434 yaitu sebesar 56,17%  sedangkan load factor terendah terdapat pada trayek 423 yaitu sebesar 9,09%. Tingkat operasi tertinggi terdapat pada trayek 54, dengan nilai tingkat operasi sebesar 100%, kemudian tingkat operasi terendah terdapat pada trayek 423 dengan nilai tingkat operasi sebesar 2,44%

A landslide that occurred on May 24, 2024, in Pekon Datarajan, Ulubelu District, Tanggamus, Lampung, caused significant disruption to provincial road access and resulted in material losses. This study aims to assess the post-failure slope stability through field geotechnical investigation and numerical analysis using the Limit Equilibrium Method (LEM), and to propose immediate countermeasures. The slope materials consist of MH (inorganic silt) and ML (elastic silt) with high moisture content and moderate to high swelling potential. The lithology is dominated by montmorillonite clay, which has hygroscopic characteristics, making it highly vulnerable to water infiltration that reduces shear strength and increases the risk of slope failure. Stability analysis indicates a post-failure factor of safety (FoS) of 1.36 (static loading) and 1.03 (dynamic loading), which decreases to 1.07 beneath raised groundwater conditions. Recommended immediate mitigation includes surface runoff control, the construction of impermeable drainage systems, the sealing of cracks using impermeable materials, and the installation of temporary slope reinforcements such as sheet piles. The implementation of these measures increased the FoS to 1.61 (static loading) and 1.16 (dynamic loading). This study provides a technical basis for the rapid and effective mitigation of landslides in areas with similar geological and hydrological conditions.

This study aims to evaluate the performance of the loading and unloading equipment in coal mining activities at the Mahakam Pit, PT Insani Bara Perkasa Site Km 11, East Kalimantan. The research was motivated by the importance of achieving mechanical equipment performance standards according to the Decree of the Minister of Energy and Mineral Resources No. 1827 of 2018. Data were obtained through direct observation and analysis of actual working time and evaluation of operational constraint factors. The results of the analysis showed that before the evaluation, the mechanical availability (MA) value was 87.24%, physical availability (PA) 88.51%, availability utilization (UA) 88.73%, and effective utilization (EU) 78.54%. After evaluating the constraint time, there was an increase in all parameters: MA to 88.71%, PA to 89%, UA increased to 90%, and EU reached 80%. This evaluation also had an impact on increasing the productivity of the loading and unloading equipment from 268.41 bcm/hour to 284.43 bcm/hour. Thus, the evaluation of work obstacles is proven to be effective in increasing the efficiency and productivity of the digging-loading equipment at the research location.

Disposal area is an area at an open pit mine that is used as a place to store or dispose of worthless materials. Disposal must also follow the specified safety factor standards, if the disposal design is not safe after being analyzed by a geotechnical engineer, the design must be redesigned to achieve the desired safety factor value. One way to increase the fk value is to make a Counterweight plan in making disposal. Where Counterweight is a fill material that is made with special treatment so that the soil bearing capacity increases which functions to withstand the load on it. Landslides on disposal slopes are one of the serious problems faced in mining activities, especially in areas with vulnerable geological and topographic conditions. PT Jembayan Muarabara, which operates in Marangkayu District, Kutai Kartanegara Regency, East Kalimantan Province, is no exception to this challenge. The A–A’ cross section shows a safety factor value of 1.118 in saturated conditions, which indicates that the slope is at a stable limit and needs to be improved through engineering such as adding counterweights. The B–B’ cross-section has a safety factor value of 2.332, which is included in the safe category and has met the provisions of the ESDM Ministerial Decree No. 1827 K/30/MEM/2018. The C-C’ cross-section has a safety factor value of 1.511, which is included in the safe category and has met the provisions of the ESDM Ministerial Decree No. 1827 K/30/MEM/2018.

Musculoskeletal Disorders (MSDs) encompassing conditions affecting muscles, bones, joints, ligaments, nerves, and tendons , are a prevalent occupational health issue, particularly in roles involving physical tasks like lifting, pushing, pulling, or carrying loads. This study aims to synthesize current scientific findings on the prevalence, contributing risk factors, and effective prevention strategies for MSDs in manual handling contexts. A systematic literature search was conducted using Google Scholar, focusing on peer-reviewed journal articles published between January 2020 and June 2025. The review identified a consistently high prevalence of MSDs, with the lower back, shoulders, neck, and upper extremities being the most commonly affected areas. Key risk factors are multifactorial, including physical/ergonomic aspects (e.g., awkward postures, heavy loads, repetitive motions, prolonged exposure, vibration) , individual factors (e.g., age, BMI, injury history) , psychosocial factors (e.g., high job demands, low job control, stress) , and organizational/manegerial factors (e.g., inadequate training, poor workstation design). The findings underscore the necessity of a holistic and integrated approach to manage MSDs.  

The port is a vital infrastructure in the global logistics chain that connects sea and land transportation. The efficiency of cargo loading and unloading operations at the port is a critical factor influencing the smooth flow of goods and overall logistics costs. In this context, the use of Business Intelligence (BI) as an integrated technological system to support data collection, analysis, and presentation is becoming increasingly important for optimizing data-driven decision-making in port environments. XYZ Port, as one of the strategic ports in Indonesia, faces challenges in managing complex loading and unloading operations with increasing cargo volumes. The implementation of a BI dashboard offers a solution to visualize operational data in real-time, identify bottlenecks, and optimize resource allocation. This study aims to implement a BI dashboard for cargo handling operations at XYZ Port. The specific objectives include identifying information needs in cargo handling operations and developing a BI dashboard that suits the characteristics of port operations. The findings indicate that the dashboard effectively supports real-time decision-making and enhances operational efficiency. The study also highlights the importance of addressing technological infrastructure, human resource readiness, and system integration challenges in BI implementation.