Publikasi Universitas Mercu Buana
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Role Ambiguity and Work Family Conflict on Job Stress of Banking Employees in Bengkulu City
No full textObjectives: The objective of this study is to analyze the effect of role ambiguity and work-family conflict on job stress among banking employees in Bengkulu City.Methodology: The study used a quantitative approach with data collected from 180 respondents through purposive sampling. The participants were permanent or contract banking employees with a minimum of one year of work experience. Data analysis was conducted using Structural Equation Modeling - Partial Least Squares (SEM-PLS). Validity and reliability tests were performed, including AVE (>0.50), Composite Reliability (CR), and Cronbach’s Alpha (>0.70).Finding: All indicators met the validity and reliability criteria: The AVE values were: Role Ambiguity (0.76), Work-Family Conflict (0.74), and Job Stress (0.77). The R-Square (R²) value for Job Stress was 0.578, indicating that 57.8% of job stress variability can be explained by role ambiguity and work-family conflict. Hypothesis testing showed: Role Ambiguity had a positive and significant effect on Job Stress (β = 0.429, t = 6.215, p = 0.000), Work-Family Conflict had a positive and significant effect on Job Stress (β = 0.378, t = 5.801, p = 0.000).Conclusion: The study concludes that both role ambiguity and work-family conflict significantly increase job stress among banking employees. To mitigate this, bank management should focus on clarifying employee roles and providing programs that support work-life balance
The Influence of Green Marketing Strategy on Customer Loyalty with Mediation Role of Brand Image
No full textObjectives: The cosmetic industry has experienced significant growth, intensifying competition among beauty and personal care brands. As sustainability becomes a crucial business consideration, companies are increasingly adopting green marketing strategies to enhance their brand image and foster customer loyalty. This study examines the influence of green marketing strategies—specifically eco-labeling, sustainable packaging, green advertising, and corporate social responsibility (CSR)—on customer loyalty, with brand image serving as a mediating factor.Methodology: This study employs a quantitative approach, using survey data from 120 consumers of The Body Shop Indonesia in Jabodetabek areas. Structural equation modeling (SEM) is used to analyze the relationships between green marketing strategies, brand image, and customer loyalty.Finding: The results indicate that green marketing strategies positively influence customer loyalty, both directly and indirectly through brand image. Brand trust and perceived value play a significant role in mediating this relationship. Furthermore, authentic green marketing efforts contribute to stronger customer retention, whereas skepticism toward greenwashing diminishes brand credibility and loyalty.Practical implications of the findings provide actionable insights for brands aiming to enhance their sustainability-driven marketing efforts. Companies should focus on transparency, consistency, and consumer education to strengthen brand image and maintain long-term customer loyalty. Distinguishing authentic sustainability initiatives from greenwashing is critical in fostering trust and positive brand associations. This study contributes to the literature by providing an industry-specific analysis of the mediating role of brand image in green marketing, addressing research gaps in differentiating genuine sustainability efforts from misleading practices.Conclusion: Theoretical and practical implications underscore the importance of authenticity and transparency in green marketing communications to foster long-term customer relationships for sustainable brands
Simultaneous Toll Road Public Infrastructure and its Transaction Volume in Non-Taxable State Revenue a Case Study at PT. Hutama Karya Persero
No full textObjectives: Toll roads are vital transportation infrastructure in improving connectivity between regions in Indonesia. Apart from being a means of transportation, toll roads also contribute to state revenue through non-tax state revenue (PNBP). However, there are still limitations in understanding the extent to which toll road length and traffic volume affect PNBP.Methodology: This research uses a quantitative approach with descriptive methods. The data used is time series data from 2013 to 2023 which includes toll road length, traffic volume, and PNBP managed by PT Hutama Karya (Persero). The analysis was carried out using linear regression to test the relationship between these variables.Finding: The results showed that there is a significant relationship between the length of toll roads and traffic volume to PNBP. The increase in toll road length and traffic volume simultaneously contributes to the increase in PNBP. In addition, toll road construction also has a positive impact on local economic growth and economic diversification of communities around toll roads.Conclusion: Toll roads not only serve as a means of transportation, but also a significant source of state revenue. Therefore, this study recommends strategies to improve the efficiency of toll road infrastructure management to optimize PNBP revenue and encourage broader economic growth
KONSEP SMART LIVING PADA DESAIN INTERIOR RUANG TUNGGU PELANGGAN SEBAGAI INOVASI PERAWATAN BANGUNAN BENGKEL GAMA JAYA MOTOR
No full textGama Jaya Motor is a car repair and maintenance workshop located in Surabaya. As a business entity, Gama Jaya Motor needs to manage its property to support its operations, one of which is building maintenance. In a workshop business, the customer waiting room is one of the most important aspects of property management, as it is directly used by customers. The interior of the customer waiting room should be designed to be attractive and aesthetically pleasing while maintaining customer comfort. This can be achieved by implementing an interior design concept based on smart living. This concept integrates various smart devices based on the Internet of Things (IoT) into the interior or building design, not only to enhance customer comfort but also to improve the operational efficiency of the workshop. This study employs a design-based case study method. The design process is carried out through field observations, interviews, and an analysis of spatial and technological requirements that can be integrated. The smart devices applied in the design include automatic lighting systems, CCTV, smart switches, smart sockets, and IoT-based temperature control systems. In addition to enhancing customer comfort, the implementation of the smart living concept is also expected to improve energy efficiency and the security of the workshop environment
Social Interaction of the Visually Disabled Through Facebook Social Media at the Iss Reflexology Clinic Kebon Jeruk West Jakarta
No full textSocial media has brought many changes in communication and community interaction. This condition also occurs in the disabled community, especially the blind. This study aims to determine the social interaction through Facebook social media from blind people with disabilities at ISS Reflexology Kebon Jeruk, West Jakarta. According to Gillin and Gillin, there are two types of social processes that arise as a result of social interaction, namely associative and disassociative. This study uses a qualitative descriptive method. Blind people use Facebook social media to increase their friends, self-expression, existence and entertainment. Facebook media also allows them to work together to provide the information they need. Most of them give positive comments so that associative interactions occur. While there are also negative comments that cause disassociative interactions.
COMMUNICATION STRATEGY OF AL-GEE RENTAL TO ATTRACT CUSTOMER INTEREST
No full textThis study analyzes Al-Gee Rental’s social media communication strategy in fostering customer engagement and loyalty within the context of Society 5.0. The central issue is how the company integrates digital communication with personal interaction to attract and retain customers. The study aims to assess the effectiveness of digital-based Integrated Marketing Communication (IMC). A qualitative method was employed through in-depth interviews with customers and observation of digital interactions. Findings reveal customer engagement across cognitive (attention and feedback), affective (emotional closeness), and behavioral (retention and active participation) dimensions. The study concludes that Al-Gee’s success lies not only in strategic digital integration but also in sustaining human interaction that strengthens long-term loyalty
Hazard evaluation of box packaging process in food seasoning industry based on SNI 9011:2021
No full textMusculoskeletal disorders (MSDs), known in Indonesia as Gangguan Otot Tulang-Rangka Akibat Kerja (GOTRAK) are one of the most common ergonomic problems in the workplace, caused by poor posture, repetitive movements, and long working hours. These conditions have a negative impact on employee health and productivity and increase healthcare costs for companies. This study aims to analyze the potential for GOTRAK complaints among workers in the box packaging process in the food seasoning industry, in accordance with Indonesian National Standard (SNI) 9011:2021. This study was conducted using a quantitative approach with a Musculoskeletal Disorder Questionnaire to assess MSD complaints. Data were collected through field observation, questionnaire completion, and work posture analysis using the methods outlined in SNI 9011:2021. The research variables included work posture, work duration, and physical strain of the workers. The results of the worker interviews regarding body part complaints showed a high risk level with risk scores of 19 and 20. The most common parts of the body to experience pain were the shoulders, upper back, lower back, and hips. The results of the ergonomic assessment of the upper body in carton packing work gave a score of 38, indicating hazardous conditions that require immediate improvement. In addition, the results of the analysis were used to develop ergonomic-based improvement recommendations to increase safety and comfort in the workplace. It is hoped that this study will provide companies with guidance on how to reduce ergonomic risks in the workplace, improve workers' wellbeing and support the development of a more sustainable industry
Enhancing Liver Disease Classification Using Support Vector Machine with IQR-Based Outlier Handling
No full textLiver disease is a significant health issue that requires early and accurate diagnosis to prevent serious complications. In this study, we propose an outlier filtering approach using the Interquartile Range (IQR) to enhance the performance of the Support Vector Machine (SVM) algorithm in liver disease classification. A publicly available liver dataset consisting of 1,700 patient records with various clinical attributes was used, and the IQR method was applied to detect and remove extreme values before model training. The SVM model employed the Radial Basis Function (RBF) kernel to capture nonlinear relationships in the data. The classifier was evaluated under two conditions: without and with IQR-based outlier removal. Performance metrics including accuracy, precision, recall, F1-score, and ROC-AUC were used to assess the model. The experimental results showed that the IQR-based preprocessing improved model performance, with the accuracy increasing from 84.41% to 84.74% and the ROC-AUC score rising from 92.08% to 93.28%. Notably, the recall for the negative class improved from 84.31% to 89.76%, indicating enhanced detection of healthy patients. These findings demonstrate that outlier handling using IQR can contribute to more stable and accurate classification outcomes, especially for models that are sensitive to data irregularities such as SVM
Perbandingan Performa Algoritma Machine Learning untuk Prediksi Risiko Kesehatan dari Polusi Udara
No full textPenelitian ini menggunakan berbagai algoritma pembelajaran mesin untuk menganalisis dan memprediksi hubungan antara polusi udara dan dampak kesehatan masyarakat. Dataset yang digunakan terdiri dari 968 instances dengan 15 fitur yang mencakup indikator kualitas udara (PM2.5, PM10, NO2, SO2, O3) dan data kesehatan (kunjungan rumah sakit, mortalitas, jenis penyakit) yang dikumpulkan dari lima kota besar di Indonesia selama periode Januari-Desember 2023. Lima algoritma pembelajaran mesin dievaluasi secara komprehensif: k-Nearest Neighbors (k-NN), Naive Bayes, Logistic Regression, Support Vector Machines (SVM), dan Neural Network. Kontribusi utama penelitian ini adalah menyediakan analisis komparatif komprehensif dari kelima algoritma tersebut menggunakan evaluasi multi-metrik dan optimasi hyperparameter khusus untuk domain prediksi kesehatan berbasis polusi udara. Hasil evaluasi menunjukkan bahwa algoritma SVM memiliki performa terbaik dengan akurasi 92%, presisi 98%, recall 96%, dan F1-Score 97%. Analisis korelasi mengungkapkan bahwa PM2.5 merupakan prediktor terkuat untuk penyakit respirasi dengan koefisien korelasi 0.78 terhadap kunjungan rumah sakit. Penelitian juga menemukan efek sinergis antara PM2.5 dan NO2 yang meningkatkan risiko kardiovaskular hingga 45%. Di sisi lain, algoritma Neural Network menunjukkan performa terendah dengan akurasi 50% meskipun telah dilakukan hyperparameter tuning ekstensif, mengindikasikan ketidakcocokan arsitektur untuk karakteristik dataset ini. Algoritma Naive Bayes dan Logistic Regression menunjukkan performa moderat dengan akurasi masing-masing 83% dan 88%. Temuan penelitian ini dapat dijadikan acuan untuk pengembangan sistem monitoring kesehatan real-time dan mendukung pengambilan kebijakan kesehatan masyarakat terkait pengendalian polusi udara di wilayah urban