Publikasi Universitas Mercu Buana
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The Management of Power System Reliability in the Offshore Oil and Gas Field
Get PDFThe reliability of electric power systems is needed in offshore oil and gas field operations because disruptions can have a direct impact on oil production, costs, and company profits.Objectives: to determine the evaluation of reliability performance and propose a model for managing the power system reliability of the PHE OSES offshore oil and gas field.Methodology: A case study with data collected through observation, interviews, and analysis of relevant documents.Finding: Reliability in 2015-2016 has not reached the target but from 2017-2021 has reached the target of 97.5%, as well as availability in 2015, 2018, 2019 & 2020 has not reached the target but in 2016, 2017 & 2021 has reached the target of 95%. This resulted in the highest production losses in 2015 at 266,965 and the lowest in 2021 at 21,388 barrels of oil. The model is proposed by combining elements in risk-based asset management method, RCM method, and redesign.Conclusion: In recent years, reliability has been on target but availability is volatile. The model is proposed to maintain reliability & availability on target so that production losses can be minimized
The Effect of Education, Recruitment and Work Facilities on Employee Performance and Job Satisfaction as Intervening Variables at PT GAG NIKEL
Get PDFObjectives: The success of the company's institutions and organizations is inseparable from the support of its employees in seeking to improve their performance so that the ability and job satisfaction of its employees is very important to be given more attention to achieve the desired success or goals of the company. Therefore a company or organization must really pay attention to its employees by means of recruitment processes, education, and also work facilities that must support them. This is done in order to improve employee performance and job satisfaction.Methodology: The method used in this study is to use a quantitative descriptive method. This study uses the PLS SEM model analysis for data processing. The sample used uses a saturated sample, namely all employees of PT Gag Nikel, totaling 68 people.Conclusion: Recruitment and work facilities have a significant effect on job satisfaction. Recruitment and work facilities also have a significant influence on employee performance. While education has no significant effect on job satisfaction and education also has no effect on performance. Job satisfaction also has no significant effect on employee performance
Increasing Customer Live Streaming Engagement in Online Shopping Platforms
Get PDFNowadays, small business entrepreneurs use a new marketing tool to promote their products. This tool is named Live streaming.Objectives: This study aims to help online shop owners maintain customer live-streaming engagement so it can enhance viewers' participation through live-streaming commerce.Methodology: This study used quantitative data, utilizing a survey methodology and employing Indonesian citizens as the research's object. Respondents were obtained through Google form with 225 respondents to be analyzed using PLS-SEM. Variables were measured using a Likert scale. Finding: The result of this study suggests that interactivity, informativeness, and personalization correlate with customer engagement in live-streaming commerce.Conclusion: This research shows how to make a live streaming engagement using e-commerce which was influenced by interactivity, a response to an interaction between subscribers and streamers during live streaming. In addition, there is also informativeness that affects customer live-streaming engagement which is seen from the information provided by the streamer to customers. There is personalization which also affects live-streaming commerce. Future studies can be done in other countries by using the enormous shopping platform in their country with specific shopping platforms, specific sectors (fashion, electronics, food, and others), and measure customer live-streaming engagement using attractiveness because not many papers discuss this topic in Indonesia. Future studies also can distribute more questionnaires for more relevant and valid results and also add more factors like the increase in customer engagement in purchase intention or value co-creation
Boosting Textile Industry Growth: Adversity Quotient Meets Entrepreneurial Orientation
No full textObjectives: The worldwide market presents substantial problems for the textile sector, especially for small and medium-sized businesses. This study explores how business performance in Java Islands SMEs' textile sectors is impacted by the Adversity Quotient (AQ) and Entrepreneurial Orientation (EO). This study focuses to determine how resilience and entrepreneurial behaviour affect organisational performance using a resource-based view.Methodology: Data were collected from 277 respondents across various SME textile firms through structured questionnaires. Structural equation modelling (SEM) was utilised to analyse the data to validate the suggested connections between AI, EO, and firm performance.Finding: The findings reveal that both AQ and EO significantly impact firm performance. Specifically, AQ boost the firm's capacity to navigate challenges and exploit opportunities, while EO fosters for competitive edge. The inestigation highlights that EO mediated partially the association among AQ along firm performance, suggesting that entrepreneurial behaviors amplify the significant effects of resilience on organizational outcomes.Conclusion: These results offer valuable insights for SME textile firms, figuring the valuable of cultivating high AQ and nurturing an entrepreneurial culture to improve performance. The study participates to the conceptual grasp of AQ and EO within the confine of emerging markets and provides practical recommendations for industry stakeholders to enhance their competitiv
Technologically Influential Hospitality: Recognizing the Drivers of Smart Hotel Visitation
No full textObjectives: Following the concept of smart hotels, this study aims to analyze the relationship between technology readiness, amenities, perceived usefulness (PU), perceived ease of use (PEOU), and visiting intentions. In addition, this study seeks to identify specific elements of technology amenities that significantly influence guests' intention to visit. Thus, this study is expected to fill a gap in the literature and propose a more comprehensive conceptual framework for understanding guest behavior in the context of smart hotels.Methodology: This study used quantitative research methods with the unit of analysis being visitors to five-star hotels in Jakarta. Purposive sampling was used to select participants who met the research criteria, resulting in a total of 290 respondents. Data collection was conducted using an online questionnaire distributed through social media. Data analysis techniques used in this study included Partial Least Squares - Structural Equation Modeling (PLS-SEM) to test the relationship between variables.Finding: The results indicate that technology amenities significantly affect PEOU, PU, and visiting intention. Meanwhile, technology readiness affects PEOU and PU but does not directly influence visiting intention. PU and PEOU mediate the influence of TR and TA on visiting intention, indicating that perceptions of ease and usefulness are the main mechanisms that bridge the relationship between technological factors and consumer behavior.Conclusion: This study concludes that technology amenities have a significant effect on PEOU, PU, and visit intention. Meanwhile, technologyl readiness affects PEOU and PU but does not directly affect visit intention. PU and PEOU become mediating variables of the effect of TR and TA on visit intention
Indonesia rupiah currency detection for visually impaired people using transfer learning VGG-19
No full textPeople with visual impairments often face difficulties in determining the authenticity of paper money, which is a crucial skill to avoid fraud. The limitations of traditional methods, like blind codes for visually impaired people, require a more advanced and efficient solution. Previous methods of currency detection using Convolutional Neural Network (CNN) techniques, including the VGG-19 architecture, have often encountered challenges, particularly the long training times required. Therefore, we propose using transfer learning techniques and modifying the top layers of the VGG-19 model, known as fully connected layers, within a mobile application with audio feedback built using Android Studio. These modifications involve substituting the three fully connected layers with dense and flattened layers. We also implemented hyperparameter tuning, including adjusting the batch sizes and setting the number of epochs. The datasets used Indonesian Rupiah paper currency from the 2022 emission year, specifically Rp 50,000 and Rp 100,000 denominations. The best transfer learning VGG-19 model achieved a batch size of 32 and an epoch of 50, resulting in a high accuracy of 88%. Response speed testing with performance profiling on Android Studio showed an overall average response time of 458 ms. The main advantage of using transfer learning with the VGG-19 model is that it significantly reduces training time while still achieving high accuracy, differentiating this work from previous studies that relied on training from scratch, which is more time-consuming and resource-intensive. Therefore, this mobile app can be categorized as having a fast response time
Comparative study of CNN techniques for tuberculosis detection using chest X-ray images from Indonesia
No full textConvolutional neural networks (CNNs) represent a popular deep-learning approach for image classification tasks. They have been extensively employed in studies aimed at classifying tuberculosis (TB), coronavirus disease 2019 (COVID-19), and normal conditions on chest X-ray images. However, there is limited research utilizing Indonesian data, and the integration of CNN models into user-friendly interfaces accessible to healthcare professionals remains uncommon. This study addresses these gaps by employing three CNN architectures—AlexNet, LeNet, and a modified model—to classify TB, COVID-19, and normal condition images. Training data were sourced from both a local hospital in Indonesia (RSUP dr. Rivai Abdullah) and an additional online dataset. Results indicate that AlexNet achieved the highest accuracy, with rates of 97.52%, 64.45%, and 92.43% on the Kaggle dataset, the RSUP Dr. Rivai Abdullah dataset, and the combined dataset, respectively. Subsequently, this model was integrated into a user interface and deployed for testing using new data from the RSUP Dr. Rivai Abdullah dataset. The web-based interface, powered by the Gradio library, successfully detected 7 out of 10 new cases with 70% accuracy. This implementation may enable medical professionals to make preliminary diagnoses
Instrumented model slope to investigate the influence of rainfall and slope gradient on matric suction
No full textPrior researchers indicated that prolonged and heavy rainfalls primarily trigger major landslides in Malaysia. This study was carried out to investigate the influence of rainfall on the matric suction of silty sand slopes through a small-scale model. A 35° and 45° slope (namely EXP1 and EXP2) models were built using soil samples from the former landslide site at Kemensah Heights, Selangor, Malaysia. Two types of sensors were used to measure matric suction and rainfall intensities using Watermarks 200SS Soil Moisture Sensor and Hydreon rain gauge RG-15, respectively. The elapsed time since the beginning of the rainfall was recorded using two cameras placed at the front and side of the slope model to observe progressive failure. The results showed that the initial matric suction with a value of 250 kPa is significantly reduced and approached 0 kPa when the range of cumulative rainfall intensity is between 30 and 36.75 mm/min and 5.25 and 6.75 mm/min recorded by PP1 and PP2 in EXP1 and EXP2, respectively. The results indicate that the reduction in matric suction induced by rainwater infiltration is the triggering mechanism of slope failure. It has also been noticed that rainfall infiltration increases with decreasing slope gradients. However, a small gradient slope requires longer rainfall prior to failure. A slope with a high gradient has a longer time before failure occurs after loss of matric suction than a low slope gradient
Car seatbelt monitoring system using real-time object detection algorithm under low-light and bright-light conditions
No full textSeatbelt usage is essential for minimizing injury risk during vehicular accidents. The monitoring seatbelt system in modern vehicles can be easily tricked into not displaying the warning alert. Car seatbelt detection, utilising real-time object detection, is employed to monitor seatbelt usage. However, the accuracy of such systems needs to be further evaluated under low-light and bright-light conditions. This study aims to develop a car seatbelt monitoring system using a real-time object detection algorithm, which will be tested in low-light and bright-light scenarios. The system integrates a trained YOLOv5 model into embedded hardware, which interfaces directly with the vehicle’s ignition system, enabling or disabling engine start based on seatbelt usage. Notifications are also delivered through LEDs, a buzzer, and Telegram messages. This system has an accuracy of 95.75%, precision of 99.1%, recall of 96.2%, and an F1-score of 97.2%. The results show that the system can generate a better confidence score under bright-light conditions than under low-light conditions. This work offers tangible proof of the efficacy of applying intelligent object detection models for real-time driver monitoring, particularly in enhancing compliance through physical intervention and IoT-based alerts
Spatial decision-making model for priority development of Indonesia coast guard stations
No full textIndonesia Coast Guard (IDNCG) is a paramilitary agency in charge of security and safety patrols in Indonesian maritime waters. The research objective is to develop priorities for the development of 35 IDNCG stations are expected to be constructed within 3 years and are considered priority project to face the increasing threats at sea. However, there is presently no system to provide support for the scientific solutions to prioritize station development despite the need for immediate decisions. This research was used to design model for determining station development priorities using the integration method of Geographic Information Systems (GIS), Analytical Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). GIS was used as an effective tool for identifying and taking measurements in certain areas. Meanwhile, multi-criteria decision-making (MCDM) methods such as AHP and TOPSIS provided structural and pairwise quantification, as well as comparisons between elements and criteria for ranking station construction priorities. The most suitable alternative stations to be prioritized were determined by integrating the three methods which were classified as cost-effective for decision-making. Model was based on four criteria, including distance to Archipelagic Sea Lanes (ASL), Distance to the port, vulnerability coverage, and vessel density coverage. Stations were ranked based on a three-year development plan. The location ranking is then expressed in the form of a map to be used by policy makers in determining priorities for developing IDNCG Stations which will have an impact on increasing security and safety in Indonesian waters