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Project-Based Learning (PjBL) is a learning method that emphasizes students' active involvement in completing real-world projects relevant to nursing education. Evaluating the implementation of PjBL is essential to assess its application at the Faculty of Nursing, Universitas Riau. This study aimed to analyze the implementation of the PjBL method among nursing students at Universitas Riau. The study employed a descriptive evaluative quantitative design with a cross-sectional approach. A total of 123 fourth-semester students were selected using a purposive sampling technique. The research instrument was a closed-ended questionnaire consisting of 25 Likert-scale items that had been validated through expert judgment and demonstrated good reliability with a Cronbach’s alpha coefficient of 0.80. The instrument covered the dimensions of project planning, collaboration and communication, motivation and creativity, critical thinking and independence, understanding and application of learning materials, interest and satisfaction, as well as lecturer assessment and feedback. Data were analyzed using univariate analysis with frequency and percentage distributions. Most respondents were 20 years old (55.3%), female (87.0%), and had a Semester Grade Point Average (SGPA) and Cumulative Grade Point Average (CGPA) above 3.50. The implementation of PjBL was categorized as high (63.4%), moderate (35.8%), and low (0.8%). Overall, the implementation of PjBL was considered optimal and effectively supported students’ active engagement, collaboration, and understanding of learning materials.

The purpose of this study is to identify the level of influence  of job description and workload on the job satisfaction of monthly contract employees at PT Multi Garmenjaya. Through  a cross-sectional  survey method, this study applies a descriptive and associative research design. The data collection was carried out through the distribution of a combination  of online (Google Form) and offline (print questionnaire) questionnaires to 87 respondents who were selected as a sample of the entire population totaling 677 monthly contract employees. Based on the results of hypothesis testing, it was found that the position description variable had a positive and partially significant influence on employee job satisfaction, with a calculated t-value of 5.529 and a significance level of 0.0000. On the other hand, the workload variable was also found to show a positive and significant influence on employee job satisfaction partially, with a calculated t  value of 1.327 and a significance value of 0.188. When tested simultaneously, the two independent variables were proven to have a significant effect on the job satisfaction of contract employees, with  an F score of 27.772 and a significance value of 0.0000. As for the Adjusted R Square value,  a value of 0.384 was obtained. This figure means that the ability of the variable job description and workload in explaining the ups and downs of the job satisfaction of PT Multi Garmenjaya's monthly contract employees is 38.4%. Meanwhile, the other percentage, which is 61.6%, is influenced by other factors or variables that are not studied and studied in this research model.

Project-Based Learning (PjBL) is a learning method that emphasizes students' active involvement in completing real-world projects relevant to nursing education. Evaluating the implementation of PjBL is essential to assess its application at the Faculty of Nursing, Universitas Riau. This study aimed to analyze the implementation of the PjBL method among nursing students at Universitas Riau. The study employed a descriptive evaluative quantitative design with a cross-sectional approach. A total of 123 fourth-semester students were selected using a purposive sampling technique. The research instrument was a closed-ended questionnaire consisting of 25 Likert-scale items that had been validated through expert judgment and demonstrated good reliability with a Cronbach’s alpha coefficient of 0.80. The instrument covered the dimensions of project planning, collaboration and communication, motivation and creativity, critical thinking and independence, understanding and application of learning materials, interest and satisfaction, as well as lecturer assessment and feedback. Data were analyzed using univariate analysis with frequency and percentage distributions. Most respondents were 20 years old (55.3%), female (87.0%), and had a Semester Grade Point Average (SGPA) and Cumulative Grade Point Average (CGPA) above 3.50. The implementation of PjBL was categorized as high (63.4%), moderate (35.8%), and low (0.8%). Overall, the implementation of PjBL was considered optimal and effectively supported students’ active engagement, collaboration, and understanding of learning materials.

This study examines the effectiveness of the GOOL (Dukcapil Go Online) service in accelerating the issuance of birth certificates at the Population and Civil Registration Office of Probolinggo City. GOOL is a digital-based civil administration service innovation that allows residents to process civil documents without visiting the office in person. This study employed a descriptive qualitative method, with data collected through in-depth interviews, observation, and documentation. Effectiveness indicators were based on Campbell's (2014) theory, covering: program success, goal achievement, community satisfaction, and overall objective attainment. The findings indicate that the GOOL service is generally effective in expediting birth certificate issuance. Supporting factors include collaboration with healthcare facilities (Indonesian Midwives Association and hospitals), an integrated 3-in-1 service program, and adequate technological infrastructure. Inhibiting factors include technical difficulties during document uploads, unstable internet connections, and limited digital literacy among some residents.

Independent Nursing Practice (INP) is a form of healthcare service that provides direct care to the community, including Homecare services. Public interest in these services is influenced by various factors; however, the dominant factors affecting interest in the Tambah Rejo area have not been clearly identified. This study aimed to identify and analyze factors associated with interest in Homecare services at independent nursing practices and to determine the most influential factor. This study employed a quantitative approach using an analytical survey design with a cross-sectional method. A total of 153 respondents were selected through purposive sampling. Data were collected using questionnaires and analyzed using the Chi-square test and multiple logistic regression. The results showed significant relationships between economic factors (p = 0.023; OR = 2.187), distance (p = 0.003; OR = 0.361), comfort (p < 0.001; OR = 49.67), service quality (p = 0.009; OR = 0.404), family support (p < 0.001; OR = 52.62), patient satisfaction (p < 0.001; OR = 0.212), and interest in Homecare services. Multiple logistic regression analysis revealed that comfort was the most dominant factor influencing interest in Homecare services (p < 0.001; OR = 0.124). Comfort was identified as the strongest determinant affecting community interest in Homecare services at independent nursing practices. Therefore, improving comfort in service delivery should be a primary priority in the development of independent nursing practices.

This research examines the influence of Price, Income, Taste, Promotion, Location, and Product Quality on consumer demand at Coffee Shops in Pekanbaru City. The population consists of Coffee Shop customers in Pekanbaru City. A nonprobability sampling method with Accidental Sampling technique was applied, involving 100 respondents. Data were analyzed using SEM-PLS approach through SmartPLS 4.0 software. The findings reveal that Price, Promotion, and Product Quality significantly influence consumer demand. In contrast, Income, Taste, and Location do not show a significant effect. Among all variables, Product Quality emerges as the most dominant factor affecting consumer demand at Coffee Shops in Pekanbaru City. Therefore, coffee shop managers in Pekanbaru City need to improve taste consistency, menu variety, presentation, and product quality standards to maintain and increase consumer demand. This research is expected to provide business owners with a basis for formulating more appropriate, competitive, and sustainable customer satisfaction-oriented marketing strategies in the local market.

Independent Nursing Practice (INP) is a form of healthcare service that provides direct care to the community, including Homecare services. Public interest in these services is influenced by various factors; however, the dominant factors affecting interest in the Tambah Rejo area have not been clearly identified. This study aimed to identify and analyze factors associated with interest in Homecare services at independent nursing practices and to determine the most influential factor. This study employed a quantitative approach using an analytical survey design with a cross-sectional method. A total of 153 respondents were selected through purposive sampling. Data were collected using questionnaires and analyzed using the Chi-square test and multiple logistic regression. The results showed significant relationships between economic factors (p = 0.023; OR = 2.187), distance (p = 0.003; OR = 0.361), comfort (p < 0.001; OR = 49.67), service quality (p = 0.009; OR = 0.404), family support (p < 0.001; OR = 52.62), patient satisfaction (p < 0.001; OR = 0.212), and interest in Homecare services. Multiple logistic regression analysis revealed that comfort was the most dominant factor influencing interest in Homecare services (p < 0.001; OR = 0.124). Comfort was identified as the strongest determinant affecting community interest in Homecare services at independent nursing practices. Therefore, improving comfort in service delivery should be a primary priority in the development of independent nursing practices.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

This study aims to analyze the effect of public satisfaction on political participation in the 2024 single-candidate regional election (Pilkada) in Batanghari Regency. Political participation in elections is an important indicator of democratic quality, especially in a single-candidate contest where electoral competition is limited. The research employed a quantitative explanatory approach with a sample of 151 respondents selected through simple random sampling. Data were collected using structured questionnaires and analyzed using simple linear regression with IBM SPSS Statistics to determine the relationship between public satisfaction and political participation. The results indicate that public satisfaction has a positive and significant effect on political participation, with a coefficient of determination (R²) of 0.510. This means that 51% of the variation in political participation can be explained by public satisfaction, while the remaining percentage is influenced by other factors not included in this study. However, voter turnout in the 2024 election declined compared to the previous regional election. These findings suggest that public satisfaction is not the sole factor influencing political participation, as the level of political competition in a single-candidate election also plays an important and contextual role in shaping voter behavior and turnout.

Game collaboration branding has emerged as a significant marketing strategy influencing player purchasing behavior. This study aims to analyze the influence of collaboration branding, player satisfaction, and emotional attachment on purchase intention among Honkai: Star Rail players. 280 active members of the Pompomfess community on Platform X (Twitter) participated in a quantitative survey that was analyzed using Structural Equation Modeling–Partial Least Squares (SEMPLS). The results extend the application of the Theory of Planned Behavior to digital game consumption behavior by showing that collaboration branding, player satisfaction, and emotional attachment significantly increases purchase intention. In addition to offering useful advice for game developers and marketers in creating player-oriented brand collaboration strategies, this study conceptually advances the body of knowledge on digital consumer behavior.

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.

The rapid growth of digital commerce has encouraged companies to integrate digital and physical marketing channels to create seamless and consistent customer experiences. This study aims to analyze the role of integrated marketing channels through omnichannel strategies, the utilization of Artificial intelligence (AI), and their impact on customer experience in the context of digital commerce. The study employs a Systematic literature review (SLR) approach by examining relevant scholarly articles related to omnichannel marketing, AI technologies, and customer experience. The findings indicate that integrated marketing channels supported by AI enhance service personalization, customer engagement, operational efficiency, and the quality of interactions between companies and customers. Furthermore, the implementation of omnichannel strategies contributes to higher customer satisfaction and loyalty by providing a more connected experience across multiple customer touchpoints. However, the implementation of integrated marketing channels still faces several challenges, including fragmented channel integration, technological complexity, high investment requirements, and concerns regarding customer data privacy and security. Therefore, effective management of integrated marketing channels is essential for improving customer experience while creating sustainable competitive advantages for companies in an increasingly dynamic digital era.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

The increase in internet users in Indonesia presents a significant opportunity for business actors to market products through digital marketing, which allows transactions anytime and anywhere and influences purchasing decisions through complete and real-time product information. In addition, impulsive buying behavior, especially in areas like Ponorogo, which is rich in quality rice products with attractive discounts, also contributes to increased sales, impacting customer satisfaction, loyalty, and long-term customer value. Therefore, this study aims to examine the influence of digital marketing, product information, and impulse buying on purchasing decisions, as well as the ability of purchasing decisions to mediate the effect of digital marketing, product information, and impulse buying on marketing performance. This study uses a quantitative approach with a research sample of 104 respondents who are consumers of rice products in the Legi Ponorogo market. The data collection technique employed a questionnaire distributed online. The data analysis technique used is SEM PLS. The results of the study indicate that digital marketing and product information affect purchasing decisions, whereas impulse buying does not affect purchasing decisions. Furthermore, purchasing decisions have an impact on marketing performance. The results of the indirect effect show that purchasing decisions mediate the influence of digital marketing and product information on marketing performance, while purchasing decisions do not mediate the influence of impulse buying on purchasing decisions.

This study aims to analyze the effect of personalized marketing on customer satisfaction and customer retention, as well as to explain the role of customer satisfaction as a mechanism linking marketing personalization to customers’ decision to remain with a brand. The background of this study is based on the increasing use of data-driven marketing strategies, product recommendations, personalized promotions, and digital communication tailored to customer preferences. In an increasingly competitive business environment, companies are required not only to attract new customers but also to retain existing customers through relevant, convenient, and valuable experiences. This study employed a quantitative explanatory approach, with the population consisting of customers who had received personalized marketing from a particular company or brand. The sampling technique used was purposive sampling, with the criteria that respondents had received personalized promotions and had made repeat purchases. The total sample consisted of 110 respondents. Data were collected using a structured questionnaire with a five-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling. The findings show that personalized marketing has a positive and significant effect on customer satisfaction. This indicates that promotions, recommendations, and marketing messages that are relevant to customer needs can create more positive customer experiences. Customer satisfaction is also found to have a positive and significant effect on customer retention, meaning that satisfied customers are more likely to make repeat purchases, continue using products or services, and avoid switching to competitors. In addition, personalized marketing has a direct effect on customer retention, although its effect becomes stronger when mediated by customer satisfaction. The implications of this study emphasize that companies need to develop personalization strategies that are not only data-driven but also relevant, ethical, non-intrusive, and oriented toward customer value. Therefore, personalized marketing can serve as an important strategy for improving customer satisfaction and maintaining long-term customer retention.

This study aims to analyze the influence of red tape on public satisfaction with public services in Indonesia. The research focuses on the definition of red tape, the characteristics of administrative procedures in public services, the level of public satisfaction, the influence of red tape on public satisfaction, and the factors influencing the relationship between red tape and public satisfaction. This study used a library research method with a qualitative descriptive approach. Data were obtained through collecting various literature sources such as books, scientific journals, articles, and previous research results relevant to the research topic. The results indicate that red tape is a long, complicated, and excessive bureaucratic procedure that hinders the effectiveness of public services. Furthermore, the results indicate that the quality of human resources, service transparency, bureaucratic culture, and the use of information technology are factors influencing the relationship between red tape and public satisfaction. Digitalization of public services and bureaucratic reform are important solutions to reduce red tape and improve the quality of public services in Indonesia. Thus, it can be concluded that red tape has a significant influence on the level of public satisfaction with public services. Therefore, the government needs to simplify administrative procedures and improve service quality to create effective, efficient, and community-oriented public services.

The development of the digital economy has driven increased customer interaction through online chat services, making customer satisfaction a key factor in business success. Response speed and chat service quality are two important aspects in shaping the customer experience, but previous research has tended to examine them separately. This study aims to analyze the influence of online chat services and response speed on customer satisfaction partially and simultaneously. The method used is a qualitative approach with a literature review of 12 scientific articles from 2020–2025 obtained from academic databases such as Google Scholar and SINTA. The analysis technique used is descriptive-critical through the identification, comparison, and synthesis of previous research findings. The results show that online chat services have a positive effect on customer satisfaction, primarily through interaction quality such as information accuracy, ease of use, and problem-solving ability. Response speed has also proven to be an important determinant, where a fast response significantly increases customer satisfaction. However, speed without quality has the potential to decrease satisfaction. The discussion shows that the two variables have a complementary and inseparable relationship. Online chat services function as a medium for interaction, while response speed is a quality attribute that determines the effectiveness of the service. Therefore, the integration of both in one model is the main contribution of this research in filling the literature gap, especially in the context of e-commerce in Indonesia.

This study aims to analyze the implementation of public service ethics by front office officers at the Public Service Mall (Mall Pelayanan Publik/MPP) of Samarinda City and its impact on the image of government institutions. As the frontline of public service delivery, front office personnel play a strategic role in shaping public perceptions and fostering public trust in government services. This research employed a qualitative descriptive approach, utilizing in-depth interviews with a functional licensing officer at the Department of Investment and One-Stop Integrated Services (DPMPTSP) of Samarinda City, supported by direct field observations. The findings reveal that the implementation of service ethics at the Samarinda MPP is guided by the principles outlined in Law No. 25 of 2009 on Public Services and the Minister of Administrative and Bureaucratic Reform Regulation No. 15 of 2014 concerning Service Standards. These regulations emphasize the values of integrity, professionalism, accountability, responsiveness, and inclusiveness in service delivery. Furthermore, effective coordination among service tenants, continuous improvement of employee competencies, and adaptation to digital systems such as the Online Single Submission (OSS) platform have contributed significantly to maintaining service quality. The study concludes that the consistent application of public service ethics enhances citizen satisfaction, strengthens public trust, and positively influences the image of government institutions in the community.