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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 rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.

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 research is grounded in the understanding that employees are the core of organizational sustainability, and their job satisfaction is shaped not only by daily tasks but also by the organization’s ability to manage workload and support balance between work demands and personal life. This study aims to analyze the effect of workload and work-life balance on employee job satisfaction at the Class I Correctional Center (Bapas) Makassar. Using a quantitative approach, data were collected through questionnaires distributed to 54 employees and analyzed using multiple linear regression assisted by SPSS Statistics 25. The research variables consist of workload and work-life balance as independent variables, and job satisfaction as the dependent variable. The findings indicate that workload has a positive and significant effect on job satisfaction, suggesting that employees’ perception of being able to complete tasks effectively can increase their comfort and confidence at work. Work-life balance also shows a positive and significant influence, indicating that the ability to manage both work responsibilities and personal life contributes directly to greater feelings of satisfaction, stability, and motivation in performing duties. Simultaneously, both variables significantly affect job satisfaction, emphasizing the importance for organizations to regulate workload proportionally while providing space for employees to maintain a healthy life balance. These findings highlight that effective workload management and support for work-life balance are crucial organizational investments to foster a healthy, productive, and employee-centered work environment.

Public Wi-Fi services (Wifi_STAKat) at the State Catholic College of Pontianak continue to face technical issues, such as network speed and connection stability, as well as non-technical challenges, including the responsiveness of administrators to user complaints. This study aims to analyze user satisfaction based on the five Servqual dimensions and to map improvement priorities using the Importance–Performance Analysis (IPA) method. The relationship between Servqual and IPA is explained by mapping GAP values (perception–expectation) into the four IPA quadrants to determine the urgency level of service improvements. A 4-point Likert scale was used to avoid neutral responses and strengthen the clarity of respondents’ perceptions. The results show that all dimensions have negative GAP scores, particularly responsiveness and reliability, which are directly related to technical indicators (speed, stability, coverage) and non-technical factors (responsiveness to complaints, ease of access. The study recommends integrating an IT-based monitoring system and increasing network capacity to improve service quality.

Effective communication is essential for teamwork effectiveness in healthcare, particularly in inpatient units where patient care requires coordination among multiple professionals. Internal data from Hospital X showed that more than 50% of medical incidents in the last two years were related to miscommunication among healthcare workers. In addition, the 2024 employee satisfaction survey reported that workplace communication satisfaction was only 62%, below the hospital target of 75%. This study aimed to examine the influence of effective communication on teamwork effectiveness with interprofessional collaboration as an intervening variable at Hospital X.This study used a quantitative cross-sectional design involving 226 healthcare workers, including doctors, nurses, and medical support staff. Data were analyzed using the Three-Box Method and PLS-SEM. The findings revealed that effective communication significantly influenced teamwork effectiveness both directly and indirectly through interprofessional collaboration. Interprofessional collaboration also acted as a significant mediating variable between communication and teamwork effectiveness. These results indicate that communication is a key foundation for strengthening collaboration and improving teamwork in hospitals. Therefore, hospitals should enhance communication training and interprofessional collaboration programs to improve healthcare quality and patient safety

This study aims to understand the role of E-Commerce in building customer loyalty, explain the process of loyalty formation, and assess how customers perceive service quality in relation to loyalty, using the GoFood service in Jombang as a case study. The rapid growth of online food delivery services has intensified competition, making customer loyalty a critical factor for sustainability. Employing a qualitative case study approach, data were collected through in-depth interviews with 30 GoFood customers and several drivers in the Jombang area. The findings reveal that E-Commerce platforms significantly enhance loyalty through user-friendly application interfaces, supporting features (such as live tracking, history, and digital payments), and beneficial promotions. The loyalty formation process occurs gradually through consistent positive experiences, moving from customer satisfaction to trust, and ultimately to habitual use. Crucially, the quality of driver services—including politeness, effective communication, punctuality, and order accuracy—emerged as a key determinant of customer comfort and repeat orders. This study implies that for E-Commerce platforms to maintain a competitive edge, strategies must integrate digital convenience with consistently reliable human interactions. The research contributes empirical insights from a semi-urban Indonesian context, highlighting that customer loyalty is not merely transactional but is built on a combination of technological ease, economic value, and positive interpersonal service experiences.

Social media has evolved into a significant platform where consumers freely express their opinions, experiences, and levels of satisfaction regarding various products, including those offered by Micro, Small, and Medium Enterprises (MSMEs). The comments and reviews shared by customers on these platforms contain diverse sentiments that can serve as valuable indicators of how consumers perceive product quality. Understanding these sentiments is crucial for MSME owners, as it allows them to evaluate their products and adapt to market expectations more effectively. This study aims to analyze customer sentiment toward MSME products on social media by utilizing the Naïve Bayes algorithm, a widely used classification method in text mining. The data used in this research consist of customer comments collected from various social media platforms. The research process involves several stages, including data collection, manual labeling of sentiments, text preprocessing (such as tokenization, case folding, and stopword removal), and splitting the dataset into training and testing subsets. Subsequently, the classification process is carried out using the Naïve Bayes algorithm to categorize sentiments into positive, negative, and neutral classes. The results of this study demonstrate that the Naïve Bayes method is effective in classifying customer sentiments with a satisfactory level of accuracy. These findings provide a comprehensive overview of consumer perceptions regarding the quality of MSME products. Furthermore, this research is expected to assist MSME business owners in understanding customer feedback more systematically and using it as a basis for improving product quality and enhancing customer satisfaction in a competitive digital marketplace.

This study aims to analyze the level of student satisfaction in paying tuition fees (UKT) through the BRImo application at Universitas Negeri Gorontalo. The research applies the service quality (SERVQUAL) framework, which consists of five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. A qualitative descriptive approach was employed, with data collected through in-depth interviews, direct observations, and documentation. Participants included students who actively use the BRImo application for UKT payments as well as staff responsible for tuition management. Data analysis followed a systematic process involving data reduction, data display, and drawing conclusions to ensure accuracy and clarity of findings. The results indicate that using the BRImo application for tuition payment offers significant convenience and efficiency, allowing students to complete transactions without physically visiting the university payment office. Despite these benefits, several challenges were identified, including failed transactions, delays in payment confirmation, and suboptimal responses from customer service staff. Overall, the study concludes that student satisfaction with tuition payments via BRImo is considered fairly good. Nevertheless, improvements in reliability and responsiveness are recommended to further enhance the user experience and optimize the quality of service provided.  

The phenomenon of growth in Indonesia’s beauty industry has intensified competition among both global and local skincare brands, including Avoskin. This situation impacts consumer trust Instagram. Avoskin must compete to build brand trust amid the higher exposure and engagement dominance of global brands on social media. Challenges such as the presence of negative reviews and unfavorable consumer perceptions that lead to dissatisfaction represent significant threats to Avoskin’s ability to sustain brand trust. This study aims to determine the influence of electronic word of mouth and brand image of @avoskinbeauty toward brand trust. The research adopts a quantitative approach using the simple random sampling method, involving 400 active Instagram users as respondents. Data were collected through Google Forms and analyzed using IBM SPSS Statistics 30.. The T - test results show that Avoskin’s electronic word of mouth on Instagram has a positive and significant effect on brand trust, with a tcount greater than the ttable value (8.335 > 1.965) and significance < 0.001 < 0.05. Similarly, Avoskin’s brand image also has a positive and significant impact on brand trust, with a tcount greater than the ttable value (22.462 > 1.965) and significance < 0.001 < 0.05. The F - test results indicate that electronic word of mouth and brand image simultaneously have a significant effect on brand trust, with an Fcount greater than the Ftable value (870.240 > 3.02) and significance < 0.001 < 0.05. In conclusion, electronic word of mouth and brand image play essential roles in enhancing brand trust. The implication of this study is that skincare companies should continuously strengthen their digital presence, consistently manage their brand image, and actively facilitate and respond to electronic word of mouth, especially on social media platforms.

This study is motivated by the importance of maintaining consumer satisfaction amidst increasingly fierce competition in the culinary business, where Warteg Bunana faces challenges in the form of a decline in the number of customers over the past two years. The objective of this research is to determine and analyze the influence of social media promotion, location, and perceived value on consumer satisfaction at Warteg Bunana in Batam City. The research method used is a quantitative approach with a survey method through the distribution of questionnaires to 100 respondents selected using simple random sampling techniques. Data were analyzed using multiple linear regression analysis via SPSS software. The findings indicate that simultaneously, social media promotion, location, and perceived value have a significant effect on consumer satisfaction with an F value of 21,940 and a significance value of 0.000 < 0.05. Partially, all three variables also have a significant influence on consumer satisfaction. The coefficient of determination (R Square) of 0.407 shows that these variables explain 40.7% of consumer satisfaction. The implications of this research suggest that Warteg Bunana management needs to increase social media promotion consistently and maintain location comfort and service quality to improve consumers' perceived value on a sustainable basis

This research is motivated by the phenomenon of decreasing number of customers at Emdee Easy Beauty Clinic Batam, which indicates the need for an evaluation of marketing strategies. The purpose of this study is to analyze the influence of price, promotion, brand image, and product quality on consumer satisfaction. The research method used is quantitative associative with a sample of 91 respondents taken using simple random sampling technique. Data were collected through questionnaires and analyzed using multiple linear regression. The results showed that simultaneously, price, promotion, brand image, and product quality had a significant effect on consumer satisfaction (F count 14.111 > F table 2.47). Partially, the variables of price, promotion, and brand image have a positive and significant influence, but product quality does not have a significant effect on consumer satisfaction in this study. The implication of these findings is that clinic management needs to prioritize competitive pricing strategies, strengthen promotional activities, and maintain a positive brand image to sustain and increase customer satisfaction.

This study aims to analyze the effect of price and e-service quality on e-satisfaction at Ninetech Store on the Shopee marketplace, both partially and simultaneously. This study uses a quantitative method with an associative approach. The research subjects were Ninetech Store customers, with a sample size of 96 respondents obtained through sampling techniques using the Rao Purba formula. Data were collected through questionnaires and analyzed using validity tests, reliability tests, classical assumption tests, simple and multiple linear regression analysis, correlation coefficients, determination coefficients, and hypothesis testing. The results show that price has a positive and significant effect on e-satisfaction, as does e-service quality, which also has a positive and significant effect on e satisfaction. In addition, price and e-service quality were simultaneously proven to have a significant effect on the e-satisfaction of Ninetech Store customers on the Shopee marketplace. The results of this study are expected to be taken into consideration by Ninetech Store in formulating pricing strategies and improving the quality of electronic services to increase customer satisfaction.

The rapid development of technology accompanied by increasing industrial competition makes human resources a determining factor for organizational success. In this context, job satisfaction is an important indicator because it is closely related to individual welfare and employee productivity. This study aims to analyze the influence of work life balance, burnout, and motivation on the job satisfaction of employees in the production department of PG Kedawoeng PT Sinergi Gula Nusantara, Pasuruan Regency. This study uses a quantitative approach. The study population includes all permanent employees of the production department as many as 64 people, with census sampling techniques so that the entire population is used as respondents. Data analysis was carried out using multiple linear regression. The results showed that simultaneously work life balance, burnout, and motivation had a significant effect on job satisfaction (p=0.000; Adjusted R²=81.1%). Partially, work-life balance had no significant effect (p=0.386), burnout had a negative but insignificant effect (p=0.082), while motivation had a significant positive effect on job satisfaction (p=0.000). The motivation variable was the most dominant factor with a contribution of 76.1%, followed by burnout at 6.0% and work life balance at 0.6%.

The advancement of digital technology has encouraged e-commerce platforms to adopt interactive features such as Virtual Try-On to enhance a more visual and personalized shopping experience. This feature allows consumers to virtually try products, thereby assisting in product evaluation prior to purchase decisions. This study aims to analyze the effect of experiential value on customer engagement behavior, with customer satisfaction as a mediating variable. The research employs a quantitative approach through a survey of 150 respondents in Indonesia who have used Virtual Try-On, using a purposive sampling technique. Data were collected through questionnaires and analyzed using Partial Least Squares (PLS). The results indicate that experiential value has a positive and significant effect on both customer satisfaction and customer engagement behavior. Furthermore, customer satisfaction also has a positive effect on customer engagement behavior and partially mediates the relationship between experiential value and customer engagement behavior. These findings suggest that valuable technology-driven experiences can enhance customer satisfaction and encourage more active consumer engagement. This study contributes theoretically to the literature on digital consumer behavior and offers practical implications for e-commerce platforms in optimizing Virtual Try-On features.

This study aims to analyze the influence of work discipline, professionalism, and organizational culture on organizational commitment among employees in the Public Service Sector. Organizational commitment is an important factor that reflects employee loyalty and attachment to the institution, while the three independent variables are considered as internal factors that can strengthen this commitment. The method used in this study is associative quantitative with a multiple linear regression approach. Data were collected through distributing questionnaires to 46 respondents based on probability sampling techniques. Data processing and analysis in this study used SPSS software version 27. Based on the results of the study, it was found that there is a significant influence of work discipline on organizational commitment. In addition, professionalism has a significant effect on organizational commitment, organizational culture has a significant effect on organizational commitment. Based on simultaneous hypothesis testing, it is proven that work discipline, organizational culture, and professionalism jointly influence organizational commitment. While the amount of contribution is 54% to organizational commitment, while the remaining 46% of organizational commitment is influenced by other factors such as leadership style, motivation, competence, rewards, job satisfaction, and employee performance. Thus, this study confirms that to increase organizational commitment, government agencies need to strengthen a healthy work culture, enforce discipline, and encourage a professional attitude in the work environment.