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Delivery delays pose a major challenge in the e-commerce industry, often leading to decreased customer satisfaction and negatively impacting business operations. In this study, the XGBoost (Extreme Gradient Boosting) algorithm is applied to predict delivery delays based on a dataset containing 96,476 records. These records include various features relevant to the delivery process, such as shipping distance, carrier performance, and order characteristics. The model achieves a high overall accuracy of 93.24%, indicating strong general performance. In particular, XGBoost demonstrates excellent results in predicting on-time deliveries, achieving a precision of 93% and a recall of 100%. However, the model struggles to correctly identify delayed deliveries. The recall for delayed deliveries is 0%, and the F1-score is extremely low at 0.01. This significant discrepancy reveals a critical limitation in the model's performance — the inability to detect minority class cases (delayed deliveries) due to class imbalance within the dataset. The results highlight the importance of addressing data imbalance in predictive modeling for delivery outcomes. When the dataset is dominated by on-time delivery records, the model tends to be biased toward that class, failing to learn the patterns associated with delays. To improve performance, the study recommends integrating class balancing techniques such as SMOTE (Synthetic Minority Oversampling Technique) to generate synthetic samples of the minority class. Additionally, the use of alternative evaluation metrics beyond accuracy — such as precision, recall, and F1-score for each class — is suggested to provide a more comprehensive understanding of model effectiveness. Overall, the study provides valuable insights into the complexities of predicting delivery delays and outlines practical strategies for enhancing future models in e-commerce logistics analytics.

This qualitative case study investigated the factors and impacts of English language learning anxiety among students at SMP Muhammadiyah Tanjungpinang. The research focused on students from the 7th, 8th, and 9th grades during the academic year 2024/2025. A total of 32 students across all grade levels were involved in the study. The researchers initially conducted classroom observations to identify students who exhibited signs of anxiety during English lessons. Based on these observations, eleven students were selected as participants for semi-structured interviews and more detailed classroom observations. The research aimed to explore how anxiety manifests in the classroom and how it affects students' language acquisition in a unique socio-educational environment. The data collected through interviews and observations were analyzed qualitatively by interpreting students’ responses and behavioral patterns in class. The findings revealed that three primary types of language anxiety—Communication Apprehension, Test Anxiety, and Fear of Negative Evaluation—were commonly experienced by the students. These forms of anxiety were often interconnected, compounding the emotional barriers students faced in English learning. One of the key contributing factors was the students’ fear of peer ridicule, especially within a tightly bonded student community. Many of the participants were affiliated with orphanages connected to the school, which created a unique emotional and social environment. This setting, while supportive in many ways, also contributed to heightened sensitivity to peer judgment and a strong fear of making mistakes. As a result, the affective filter among these students was notably high, significantly hindering their willingness to participate and ultimately affecting their English language acquisition.

This study aims to analyze the correlation between learning models and student achievement at SMA Negeri 1 Kuala by applying the Apriori algorithm in data mining, using Rapid Miner software as the primary tool for analysis. The research is motivated by the shift in educational approaches from conventional teacher-centered methods toward more innovative strategies such as project-based learning and cooperative learning, which are expected to foster higher levels of student engagement and improve academic outcomes. In many schools, particularly at the secondary level, the choice of learning model, availability of facilities, and attendance rates are crucial factors that shape learning effectiveness and student performance. The data collected in this study include student grades, the types of learning models implemented, school facility conditions, and attendance rates for the 2023/2024 academic year, covering a total of 680 students. The Apriori algorithm was employed to discover hidden patterns and associations among these variables, enabling the identification of relationships between learning factors and academic achievement. By applying Rapid Miner software, the research systematically generated association rules that reflect meaningful correlations in the dataset. The results indicated that the use of the Indonesian language subject in combination with a cooperative learning model, adequate and complete school facilities, and good student attendance was strongly associated with the attainment of an A grade. This finding was supported by a support level of 53.33% and a confidence level of 100%, suggesting a robust and reliable relationship between these factors. The implementation of data mining techniques through Rapid Miner not only allowed for efficient data processing but also provided practical recommendations for educators and school administrators in designing effective instructional strategies.

Indonesia is prone to natural disasters because it is located at the confluence of three active tectonic plates. This condition causes high earthquake, volcano, and tsunami activity in Indonesia. Mount Kelud is the most active volcano in Indonesia with cycles that recur every 8 to 15 years. The community service method carried out is to collect data on the area, population, targets, capacity, vulnerability level, and empirical data on the 2014 eruption of Mount Kelud. Then conduct analysis, calculate estimates of health logistics needs, especially reproductive health, socialize the results of the analysis, and conduct disaster preparedness education. This activity was carried out for 6 weeks from March 12 to April 21, 2025. Based on the results of the risk assessment, the Ngancar District, Kediri Regency area has a score of frequent risk scale, severe impact scale, and priority and impact scale in the high category. To overcome the health crisis, a contingency plan is needed, especially for the reproductive health sub-cluster, which includes the preparedness of target data, existing capacity in the region, the level of vulnerability, and the estimated amount of health logistics needed to anticipate the eruption of Mount Kelud. Mount Kelud has a periodic eruption pattern in 8 to 15 years. The contingency plan for dealing with the health crisis of the eruption of Mount Kelud is very important for health service stakeholders because it can minimize the adverse impacts caused, increase rapid response, and ensure smooth coordination between related institutions in dealing with the natural disaster effectively and efficiently. It also supports disaster risk reduction efforts at the community level and strengthens the resilience of local communities.

Improving student discipline is one of the main challenges in the education system. This study explores the application of persuasive communication patterns in improving the discipline of high school students in West Bandung with the SPEAKING approach from Dell Hymes. This approach identifies relevant communication components, including settings, participants, goals, and norms, to produce more effective interactions between teachers and students. This study uses qualitative methods with in-depth interviews and participant observations to analyze the application of persuasive communication strategies in the school environment. The results of the study indicate that the Persuasive communication pattern is able to build more harmonious relationships, foster intrinsic motivation, and increase student compliance with school regulations.

This research aims to develop a recommendation system that can help retail business owners design more effective, data-driven promotional strategies. This system utilizes data mining techniques and the Apriori algorithm to extract association rules from consumer transaction data, thereby identifying more specific and accurate consumer purchasing patterns. Based on these patterns, the system can provide relevant promotional recommendations, such as product bundling, buy-one-get-one offers, or special discounts, which can attract consumer interest and increase sales. The system's implementation process is presented in the form of an interactive dashboard, which allows business owners to upload their transaction data, adjust analysis parameters, and visualize the promotional recommendation results in a way that is easier to understand and can be directly applied to their marketing strategies. This system not only provides well-structured promotional recommendations but also enables retail business owners to make more informed and efficient decisions in determining the type of promotion to implement, based on insights gained from analyzing their own transaction data. By utilizing this system, business owners can optimize their promotional strategies more efficiently and effectively, because they can quickly identify promotions that best suit consumer purchasing patterns. This can increase impulse sales, as relevant promotions will encourage consumers to purchase more products. Furthermore, this system shows great potential in increasing consumer engagement, as the promotions provided are more personalized and tailored to each consumer's preferences. Therefore, the implementation of this recommendation system has the potential to drive significant sales growth and help retail business owners achieve greater profits, as well as accelerate their business decision-making process. This system, ultimately, not only benefits business owners but also enhances the consumer shopping experience with promotions that are more tailored to their needs and preferences.

Gastritis usually occurs in people with irregular eating patterns and consuming foods that stimulate stomach acid production. Inflammation of the gastric mucosa or lining can be caused by various factors. The purpose of this study was to determine the effect of soursop leaf decoction on reducing gastritis pain. This research used a quasi-experimental design with a one-group pretest-posttest approach. The sample size was 15 people, using accidental sampling. This study was conducted from June 12 to 18, 2025. Data were obtained through observation sheets using the Numeric Rating Scale (NRS). Normality was tested using the Shapiro-Wilk test, and data analysis used the paired t-test. The results showed that before the soursop leaf decoction, the average pain score for respondents was 0.074, while after the decoction, the pain score decreased to 0.151, a decrease of 0.007 with a P-value of 0.001 (<0.05). Conclusion: The soursop leaf decoction is effective in reducing gastritis pain. Respondents are encouraged to regularly consume the soursop leaf decoction when experiencing pain, and it can serve as a reference for future research using different variables.

This corpus-based study explores the acquisition patterns of English modal verbs by Indonesian EFL (English as a Foreign Language) learners through a comprehensive analysis of learner language data. The study utilizes a specialized learner corpus consisting of 2.5 million words drawn from both written and spoken productions of 450 Indonesian learners, covering various proficiency levels. The research focuses on examining the frequency patterns, semantic distributions, and error types associated with modal verb usage across the learner corpus. The study employs a combination of quantitative corpus linguistic methods and qualitative error analysis to uncover developmental trends and persistent difficulties in acquiring English modals. The findings highlight a significant underuse of epistemic modality, which expresses degrees of certainty, and an overreliance on core modals like "can," "will," and "must." Additionally, learners systematically avoid more complex modal constructions that are semantically nuanced and less frequent in their linguistic output. The analysis also reveals notable cross-linguistic influences from Indonesian, particularly in the areas of politeness marking and the expression of certainty. These interference patterns suggest that Indonesian learners may transfer modal expressions from their native language, leading to specific errors in the usage of English modals. Based on the findings, the study proposes a usage-based pedagogical framework that integrates corpus-informed instruction with explicit semantic mapping of modal meanings. This framework encourages teachers to address modal verb acquisition by emphasizing frequency-based approaches, contrastive semantic analysis, and corpus-driven awareness-raising activities. The research suggests that by focusing on the form-meaning-function relationships of modals in authentic contexts, learners can better understand and produce English modals accurately and appropriately. The findings have significant implications for enhancing modal verb instruction in EFL classrooms, especially for Indonesian learners.

Background: Stunting remains a serious public health issue in Indonesia, particularly in rural areas such as Ambasea Village, Laeya Sub-district, South Konawe Regency. Stunting, or chronic growth failure in children due to prolonged malnutrition, generally occurs during the first 1,000 days of life. In Ambasea Village, this problem is exacerbated by irregular eating patterns among toddlers, consumption of low-nutrient foods, and poor hygiene behaviors. Toddlers frequently consume unhealthy snacks, reject main meals such as rice and side dishes, and rarely wash their hands with soap before eating or after using the toilet. Furthermore, limited access to basic sanitation—such as the lack of proper latrines and adequate wastewater disposal systems (SPAL)—also contributes to the high risk of infections that disrupt nutrient absorption, increasing the likelihood of stunting in children. Objective: This study aims to describe the environmental health conditions contributing to the incidence of stunting among children aged 0–2 years in Ambasea Village. Methods: The research used an observational analytic method with a quantitative cross-sectional design. The study involved 54 toddlers identified as stunted. Data were collected through structured interviews with parents or caregivers and direct observation of the household and surrounding environmental conditions. Results: The results showed that 66.5% of households did not have access to proper latrines, and 70% lacked adequate wastewater disposal systems. However, 87% had access to clean water, and 85% of respondents demonstrated good handwashing behavior. Conclusion: The environmental health conditions in Ambasea Village reveal ongoing challenges related to latrine ownership and wastewater management. Although clean water access is relatively good and hygiene practices among residents are fairly positive, improving sanitation infrastructure remains crucial. Enhancing these conditions is expected to significantly reduce the risk of stunting among toddlers in the area. Collaborative efforts involving local government, health workers, and the community are essential to create a healthier environment for early childhood development.

The nutritional status of elementary school children serves as a vital indicator of their overall growth, development, and future health outcomes. Poor nutritional status, whether in the form of undernutrition or overweight, can lead to a range of health and academic performance issues. This study aimed to assess the nutritional status of Grade 4A students at SD 064981 Cempaka Raya using anthropometric measurements and to examine the association between snacking habits and nutritional categories. A descriptive quantitative research design was employed, utilizing a total sampling approach involving all 20 students in the class. Data collection consisted of direct height and weight measurements conducted according to standardized procedures. The data were then analyzed using the WHO Anthro Plus software to classify nutritional status into undernourished, normal, overweight, and obese categories. Additionally, information on students’ snacking habits during school hours was obtained through structured questionnaires. The results indicated that 25% of students were undernourished, 50% had normal nutritional status, 20% were overweight, and 5% were obese. Bivariate analysis using the Chi-Square test demonstrated a statistically significant relationship (p < 0.001) between snacking behavior and nutritional status. Specifically, all students who reported frequent consumption of snacks at school were classified as overweight or obese, whereas those who did not engage in frequent snacking predominantly fell within the undernourished or normal categories. These findings highlight the potential role of unhealthy snacking patterns in contributing to excessive weight gain among school-age children. Based on the results, it is recommended that nutrition education programs be implemented for both students and parents, coupled with stricter regulations on the availability and sale of high-calorie snack foods within the school environment. Such measures may serve as preventive strategies to promote healthy growth, maintain optimal nutritional status, and reduce the risk of non-communicable diseases later in life.

This study aims to evaluate the extent to which the Shopee e-commerce platform affects the sales rate of clothes in Pasar 16 Ilir, Palembang, which is known as one of the largest clothing trading centers in South Sumatra. The background of this research departs from the phenomenon of the rapid development of e-commerce in Indonesia, where Shopee dominates the fashion category and is the main choice of consumers in online shopping. The change in consumer behavior from conventional to digital shopping patterns encourages businesses in traditional markets to adjust strategies to remain relevant and competitive in the increasingly dynamic era of digital transformation. This research method uses a combination of quantitative and qualitative approaches. A survey was conducted on 100 sellers and 150 consumers to collect data on shopping habits, perception of promotions, and the impact of using Shopee on clothing sales. In addition, in-depth interviews with several business actors at Pasar 16 Ilir were conducted to gain a more detailed understanding of the adaptation strategies they implemented. Data analysis shows that Shopee's promotional features, such as discounts, cashback, and flash sales, are the dominant factors that increase consumer interest. Hedonistic aspects, including the convenience and pleasure of online shopping, as well as customer reviews, also have a significant influence on purchasing decisions. The results of the study confirm that the integration of Shopee with the traditional market contributes to the increase in the volume and sales value of clothes in Pasar 16 Ilir. The online-to-offline (O2O) synergy model helps merchants reach a wider market and improve their competitiveness. In conclusion, optimizing e-commerce platforms through effective promotion strategies, review management, and customer service is the key for MSME actors in facing competition in the digital era.

The existence of Final Waste Processing Sites (TPA) in urban areas often presents a dilemma between the need for waste management infrastructure and its environmental and social impacts on surrounding communities. This study aims to examine the impact of the TPA Terjun in Medan City on patterns of land use change and the socioeconomic conditions of nearby residents. The method used is quantitative, involving a survey of 150 respondents, and multiple linear regression analysis to test the influence of two independent variables namely, the characteristics of the TPA and public perception and response on community perceptions of environmental impacts. The results indicate that both independent variables have a significant simultaneous effect on public perception, with a model significance value of 0.022. Partially, the physical characteristics of the TPA have a significantly positive influence, while community perceptions and responses also contribute meaningfully. However, the low coefficient of determination (R² = 0.009) suggests that many other factors outside the model also influence perceptions of environmental impact. This study highlights the importance of a holistic approach in spatial planning and urban environmental management, particularly in relation to public facilities such as TPAs. Community participation, infrastructure quality, and zoning certainty are crucial factors in maintaining the balance between the functional needs of the city and the desired quality of the microenvironment.

At the Sumatera Province Tanjung Morawa District exactly at Bangun Rejo Vilage, The high prevalence of anxiety among pregnant women in this region is influenced by high salt consumption exceeding recommendations, irregular eating patterns due to the background of the majority of the population as fishermen, and low compliance with pharmacological therapy due to concerns about side effects on the fetus. As a mitigation effort, non-pharmacological interventions were carried out in the form of music therapy and education about healthy eating patterns. This Community Service Program (PKM) aims to increase knowledge and reduce anxiety levels in pregnant women through lecture methods and the application of music therapy. The implementation method includes health education and structured music therapy. The results of the intervention showed an 89% increase in knowledge of pregnant women regarding diet, as well as a decrease in anxiety levels with an average value (mean) of 1.17 in the third to fourth week of therapy.

Innovation in the fashion industry is increasingly influenced by the integration of technology, which plays a crucial role in creating more efficient and sustainable design practices. This study explores the potential of combining fabric slashing techniques with artificial intelligence (AI) to optimize the design process, reduce textile waste, and support sustainability goals. Using a mixed-methods approach, the study involved experimentally developing an AI-based algorithm capable of automatically generating cutting patterns. Surveys and in-depth interviews with fashion designers provided qualitative insights into the acceptance, feasibility, and challenges of adopting this technology in a real-world design environment. The results indicate that integrating AI into cutting techniques reduced textile waste by up to 25%, while accelerating the design process and enabling the creation of more complex and innovative patterns compared to traditional manual methods. Furthermore, designers reported that the AI-based system not only increased efficiency but also expanded creative opportunities by presenting previously unimaginable design alternatives. The study also highlights the broader implications of AI applications in fashion innovation, particularly in adapting industry practices to global sustainability demands. By reducing waste and encouraging smarter production systems, AI has the potential to catalyze the transformation of the fashion industry towards an environmentally friendly and resource-efficient sector. The results of this study reinforce the importance of implementing cutting-edge technologies in response to growing environmental concerns and market demand for sustainable fashion. This research also makes a significant contribution to the development of modern design approaches by presenting empirical evidence of the synergistic benefits of traditional techniques and digital intelligence, while also offering practical recommendations for designers, researchers, and industry stakeholders to utilize AI as a strategy in building a sustainable fashion ecosystem that balances creativity, efficiency, and environmental responsibility.

The film Prisoners (2013), directed by Denis Villeneuve, presents a complex portrayal of emotional intensity, moral ambiguity, and psychological struggle in the aftermath of a child kidnapping. Conflict becomes the central element that shapes the characters, drives the storyline, and raises important questions about justice, resilience, and ethical boundaries. This study aims to explore the internal and external conflicts found in Prisoners, and how these tensions reflect challenges often encountered in real life. Using a descriptive qualitative method and based on William Kenney’s theory of conflict, the research closely analyzes key scenes and character interactions to identify patterns of tension and confrontation. The results show that Prisoners features 15 conflict events: internal conflict (26.67%), man vs. man (33.33%),man vs. society (26.67%), and man vs. nature (13.33%), with with man vs. man emerging as the most dominant, emphasizing the focus on intense personal struggles and confrontations between characters. The findings suggest that Prisoners (2013) uses conflict not just as a narrative device, but also as a way to invite the audience to reflect on moral choices, human limits, and the emotional cost of seeking justice in moments of crisis.

The development of digital technology has brought about significant changes in people's transaction patterns, particularly with the increasing use of online platforms for buying and selling. This phenomenon provides convenience for consumers and merchants, but is also accompanied by a high rate of online fraud experienced by both consumers and merchants. This fraud can take the form of fraudulent transactions, goods not received, or identity fraud. Low public legal literacy regarding rights and obligations in digital transactions is one of the main causes of weak legal protection for fraud victims. Many consumers and merchants are unaware of their rights and the legal procedures to take when experiencing fraud. This community service activity aims to increase the legal understanding of the public, especially online merchants and consumers, regarding digital consumer protection and legal fraud handling mechanisms. The activity implementation methods included interactive legal counseling, distribution of closed-ended questionnaires, case study simulations, Q&A discussions on legal issues, and light consultations. A total of 60 respondents, consisting of 30 merchants and 30 consumers, participated in the closed-ended questionnaire. The results showed that the majority of participants did not fully understand their rights in digital transactions and were unaware of the legal procedures to take when experiencing fraud. Despite this, participant interest in legal education was very high, with over 75% stating they wanted further legal assistance. This activity is expected to provide the public with better insight into their rights and obligations in digital transactions, as well as raise awareness of the importance of legal protection in the digital age. This is expected to make the public more vigilant and protected from potential online fraud in the future. Furthermore, increased legal literacy is expected to create a safer and more trustworthy digital transaction ecosystem for all parties.

Growth rapid computing cloud, especially on academic, government, and service platforms. public, has trigger improvement frequency and complexity Distributed Denial of Service (DDoS) attacks. Intelligent DDoS attacks AI based capable copy pattern Then cross user valid, so that difficult detected and mitigated. The majority approach mitigation moment This nature reactive, no scalable, and tends to sacrifice availability service for authorized users. Research​ This aiming develop architecture proactive and adaptive defense​ For ensure continuity service during attack ongoing. Security model proposed hybrid​ integrating Zero Trust Architecture (ZTA), adaptive bandwidth control, and isolation service container -based. Architecture consists of from three layer Main: (1) ZTA Policy Engine which performs verification identity and assessment behavior through tokens and policies intelligent; (2) Adaptive Bandwidth Load Balancer which automatically dynamic separate and arrange Then cross based on reputation and level trust ; and (3) Containerized Service Cluster which groups request to in different containers For user trusted and not known . Components addition such as blockchain -based smart contracts are used For recording request and verification access , as well as lightweight AI module used for profiling then cross in real-time. Simulation results show that this model succeed increase availability service for user trusted during attack , press false positive rate , as well as optimize allocation source power. Integration of zero trust policies with intelligence Then cross and segmentation service in real-time forming framework effective and scalable defense​ to modern DDoS threats . In conclusion , the study This contributes a robust , adaptive , and modular architectural model for maintain continuity cloud services in condition network at risk .

This study aims to analyze the electrical energy consumption of a bench-type drilling machine, RYU RDB 13, by varying machining parameters in the form of spindle speed and feed rate. Electrical energy is a critical aspect of production efficiency in the manufacturing industry, particularly in machining processes that require continuous power consumption throughout the cutting operation. The material used in this study is aluminum 6061, chosen for its lightweight, corrosion resistance, and wide application in the automotive and aerospace industries. The drilling process was carried out using three spindle speed variations: 620 rpm, 920 rpm, and 1280 rpm, along with three feed rate variations: 0.04 mm/rev, 0.08 mm/rev, and 0.1 mm/rev. Current and voltage were measured using a digital wattmeter in real-time, and energy consumption was calculated in wattseconds (Ws) using power calculation formulas. The results indicate that increasing the feed rate and spindle speed leads to higher instantaneous power consumption. However, total energy consumption tends to decrease at higher speed and feed combinations due to shorter machining times. The optimal parameter combination was found at a feed rate of 0.1 mm/rev and a spindle speed of 1280 rpm, which resulted in the lowest energy consumption of 387 Ws and the fastest drilling time. This demonstrates that selecting the right machining parameters not only improves energy efficiency but also maintains or enhances productivity. The observed power consumption pattern typically shows a sharp increase at the beginning of the drilling process, a stable phase during the main cutting stage, and a rapid decrease towards the end of the cut. These findings contribute to a better understanding of the relationship between machining parameters and energy efficiency, serving as a basis for developing sustainable production strategies in the manufacturing sector that prioritize energy savings and cost reduction.

Improving the quality of children's health is one of the main priorities in achieving the Sustainable Development Goals (SDGs), particularly in addressing stunting prevention in Indonesia. Stunting remains a serious challenge in public health development, especially among young children who suffer from chronic malnutrition. To tackle this issue, effective nutritional education is essential, especially for young mothers who play a central role in caregiving and determining their children's dietary intake. In line with the shift in information consumption patterns from conventional media to digital platforms, social media is becoming increasingly significant as a channel for health communication and education. One emerging phenomenon in this context is the rise of public figures from the medical profession actively sharing health-related content online, commonly referred to as “doctor influencers.” This study aims to analyze the digital communication strategies employed by doctor influencers, using the Instagram account @mizaafrizal, owned by Dr. Miza Afrizal, as a case study, focusing on how he educates young mothers about child nutrition. This research adopts a descriptive qualitative approach, utilizing data collection techniques such as content observation, in-depth interviews, and literature review on digital communication and health promotion. The findings indicate that Dr. Miza employs a persuasive and interactive communication strategy through the use of humanistic language, visually engaging content, and scientifically supported information in each post. He also leverages Instagram features like reels, stories, and the comment section to establish two-way communication with his followers. Dr. Miza’s credibility as a pediatrician enhances the reception of his messages. His approachable, clear, and educational style of delivery successfully captures the attention of young mothers and increases their understanding of the importance of nutrition in early childhood development. These findings highlight the influential role of doctor influencers as change agents in raising public awareness about child nutrition. Moreover, they contribute positively to digital-based health promotion efforts in Indonesia, showing the potential of social media as a powerful platform to support national health initiatives.  

This research explores the influence of customer satisfaction on the financial performance of Perumda Tirtanadi, with a particular focus on the digital service system as a moderating factor. The study is driven by the growing urgency for digital innovation in public service sectors, particularly in the wake of the COVID-19 pandemic, which significantly altered customer engagement patterns. A quantitative method is adopted, employing Partial Least Squares–Structural Equation Modeling (PLS-SEM) using the SmartPLS 4 software to process the collected data. The analysis demonstrates that both customer satisfaction and digital services have independent and significant positive effects on financial outcomes. However, the interaction between these two variables does not show a statistically significant moderating effect. These findings underline the value of digital infrastructure as a strategic internal resource that supports financial growth. Nevertheless, the minimal moderating impact suggests that a portion of customers either lack access or sufficient skills to effectively utilize the available digital platforms. This study adds to the current body of knowledge by examining the interplay between digital transformation and customer satisfaction in shaping financial performance, framed through the Resource-Based View (RBV) theory. The research suggests that improving digital literacy and promoting better adoption of digital tools among customers is essential to fully capitalize on the benefits of technological advancement. Furthermore, it highlights the need for continuous training and support to ensure that all customers can engage with digital services effectively, thereby enhancing overall satisfaction and financial performance. By addressing these gaps, organizations can foster a more inclusive digital environment that benefits both the customers and the service providers.