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Introduction: Smartphone use has increased substantially in higher education and is widely used by university students for both academic and non-academic activities. Prolonged smartphone use combined with poor posture may increase mechanical load on cervical structures and lead to neck pain. This study aimed to examine the relationship between smartphone use and neck pain intensity among students at IKES Suaka Insan. Methods: A quantitative cross-sectional study was conducted involving 55 undergraduate nursing and physiotherapy students selected using cluster sampling. Smartphone use was assessed using a structured questionnaire, while neck pain intensity was measured using the Visual Analog Scale (VAS). Data were analyzed using Spearman’s rho correlation test. Results: The analysis showed a weak negative association between smartphone use and neck pain intensity (r = -0.16), with a p-value of 0.20 (>0.05), indicating no statistically significant relationship. Conclusion: There was no significant association between smartphone use and neck pain intensity among students. Future studies should include ergonomic posture and duration of smartphone use as additional variables.

Introduction: Smartphone use has increased substantially in higher education and is widely used by university students for both academic and non-academic activities. Prolonged smartphone use combined with poor posture may increase mechanical load on cervical structures and lead to neck pain. This study aimed to examine the relationship between smartphone use and neck pain intensity among students at IKES Suaka Insan. Methods: A quantitative cross-sectional study was conducted involving 55 undergraduate nursing and physiotherapy students selected using cluster sampling. Smartphone use was assessed using a structured questionnaire, while neck pain intensity was measured using the Visual Analog Scale (VAS). Data were analyzed using Spearman’s rho correlation test. Results: The analysis showed a weak negative association between smartphone use and neck pain intensity (r = -0.16), with a p-value of 0.20 (>0.05), indicating no statistically significant relationship. Conclusion: There was no significant association between smartphone use and neck pain intensity among students. Future studies should include ergonomic posture and duration of smartphone use as additional variables.

Nursing care in hospitals is still below the established standard of 80%, thus reflecting suboptimal nurse performance. This condition is thought to be influenced by factors such as rewards, workload, length of service and supervision. This study aims to analyze the relationship between rewards, workload, length of service, and supervision with nurse performance in the Inpatient Unit of Ratu Zalecha Martapura Regional Hospital. This study used a quantitative method with an observational analytical design using a cross-sectional approach. The study sample consisted of 152 nurses selected using cluster proportional random sampling technique. Data were collected using a questionnaire and analyzed using the chi-square test and multiple logistic regression. The results showed a significant relationship between rewards and nurse performance (p-value=<0.001), workload and nurse performance (p<0.001), and supervision and nurse performance (p-value=<0.001). Length of service did not show a significant relationship with nurse performance (p-value=0,968). Multivariate analysis showed that supervision was the most dominant factor related to nurse performance. Thus, compensation, workload, and supervision are related to nurse performance, while length of service is not related to nurse performance in the Inpatient Unit of Ratu Zalecha Regional Hospital, Martapura. The hospital is expected to improve supervision, workload management, and training and recognition for nurses to improve the quality of nursing services.

Flooding remains a recurrent hazard in the Special Capital Region of Jakarta (DKI Jakarta), causing substantial disruptions across multiple dimensions community life, including social well-being and economic activities. The availability of flood-related information through the Jakarta One Data Portal (Satu Data Jakarta) provides significant opportunities for broader data utilization; however, transforming such information into meaningful assessments regional vulnerability requires a systematic analytical approach to generate more comprehensive understanding of the conditions of individual urban villages (kelurahan). This study focuses on the classification areas based on the characteristics and impacts of flood events occurring throughout DKI Jakarta. The analysis utilizes flood event records from 2023 to 2025 and incorporates several indicators, including the number of flood occurrences, the number of affected neighborhood associations (RW), the number affected households, the number of affected residents, the number of evacuees, the number of evacuation sites, and floodwater depth. Data processing was conducted using the Knowledge Discovery in Databases (KDD) framework, encompassing data selection, cleaning and preprocessing, transformation, pattern exploration, result evaluation, and knowledge extraction. The findings demonstrate that three-cluster solution effectively captures variations in flood vulnerability levels, corresponding to low-, moderate-, and high-risk categories. A total of 96 urban villages were classified as low-risk, 27 as moderate-risk, and 46 as high-risk areas. The resulting clustering patterns provide a clearer spatial representation of flood-risk distribution across urban villages, thereby offering valuable insights for the development more targeted mitigation strategies, the prioritization of flood management interventions, and the enhancement of evidence-based decision-making processes in DKI Jakarta.

This literature review synthesizes findings from fifteen peer‑reviewed studies published between 2020 and 2026 to examine the determinants of sustainable competitive advantage in the furniture industry. The analysis reveals that green innovation, environmental performance, and market orientation interact as core drivers of competitiveness, supported by theoretical perspectives including the Resource‑Based View, Natural Resource‑Based View, Institutional Theory, Circular Economy, and Strategic Management frameworks. The review highlights how internal capabilities, regulatory compliance, and responsiveness to consumer preferences collectively shape the ability of micro, small, and medium enterprises to adapt to sustainability demands in global markets. Evidence shows that eco‑innovation practices, waste recovery strategies, and clustering models enhance efficiency and legitimacy, while indicators of green growth and brand performance provide practical tools for evaluating sustainability outcomes. The synthesis underscores that competitive advantage in this sector is not determined by isolated variables but by systemic integration across resources, operations, and market dynamics. This study contributes theoretically by consolidating fragmented insights into a coherent conceptual model and practically by offering guidance for enterprises and policymakers to foster green transformation. The findings emphasize the urgency of aligning industrial practices with ecological integrity and suggest that future research should examine cross‑country variations, longitudinal impacts, and the integration of digital technologies with sustainability strategies to strengthen the resilience of furniture enterprises in the global economy.

Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

The development of information technology and the internet has increased the use of online marketplaces as sources of transaction and information, including in the used vehicle sector. OLX provides vehicle information such as price, brand, year, fuel type, mileage, and seller location, but the data is presented individually, making overall market analysis difficult. This study aims to design a used car market analysis dashboard based on OLX advertisement data in the Greater Jakarta area using a Business Intelligence (BI) approach. Data were collected through web scraping and processed through data cleaning to improve quality. Market segmentation was conducted using the K-Means Clustering method based on vehicle price, year, and mileage. A Star Schema analytical database was implemented to support data management and visualization. User information needs were identified through questionnaires to determine Measures and Key Performance Indicators (KPIs). The dashboard was developed using Microsoft Power BI and features interactive visualizations, including KPI Cards, Bar Charts, Line Charts, and Pie Charts. Results show that the dashboard presents market information in a structured and informative manner, including vehicle counts, average prices, market trends, brand and location distributions, and segmentation results. Black Box Testing confirmed that all dashboard functions operated as expected, supporting faster and more effective data-driven decision making.

Purpose Research on digitalization in Human Resource Management (HRM) has grown significantly alongside rapid digital transformation and organizational change. However, studies integrating systematic literature review and bibliometric analysis remain limited. This study aims to examine research trends and thematic developments related to digitalization in HRM through a hybrid systematic literature review and bibliometric analysis approach. Method This study employed a Systematic Literature Review based on PRISMA 2020 guidelines using data from the Scopus database with keywords related to digitalization and Human Resource Management. The initial search identified 2,497 documents, and after the screening process, 108 relevant articles were selected. Data were analyzed using VOSviewer to identify publication trends, keyword relationships, collaboration networks, and thematic clusters. Findings The findings indicate that research on digitalization in HRM increased significantly during 2018–2026. Dominant themes include digital transformation, artificial intelligence, e-HRM, innovation, Industry 4.0, sustainability, and organizational performance. Digitalization in HRM has evolved from administrative automation toward strategic organizational transformation supported by technology and data-driven decision making. Originality/value This study integrates systematic literature review and bibliometric analysis to provide a comprehensive understanding of digitalization in HRM.  

Decentralisation and democracy are two interrelated concepts in governance reform, particularly in improving the effectiveness of regional development. Decentralisation is often seen as an instrument to strengthen democracy by bringing the decision-making process closer to the people. This study aims to analyse the trend of research publications on decentralisation in Indonesia using a bibliometric analysis approach. The articles used in this study were obtained from Scopus data. From 472 articles found in the scopus database between 1999 and 2025. The selected articles were then managed using biblioshiny and Vosviewer software. The results show that publications related to decentralisation have fluctuated over the last 27 years. The article with the most citations entitled Decentralisation and Democracy in Indonesia: A Critique of Neo-Institutionalist Perspectives has 213 citations. Meanwhile, the highest affiliation shows that the University of Indonesia is the institution with a total of 25 publications. The mapping of articles based on the relationship between keywords (co-occurance) is formed into 8 clusters, each cluster describes topics that are often discussed in decentralisation-related literature such as Indonesia, decentralization, democracy, local government, governance approach, election, Asia and southeast Asia.

Dengue Hemorrhagic Fever (DHF) remains a major public health problem in Indonesia, particularly in densely populated areas. Control efforts require accurate data and spatial analysis to understand disease distribution patterns. Geographic Information System (GIS) is an effective tool for visualizing case distribution and supporting surveillance and planning of control programs at the primary healthcare level. This study aims to describe the spatial distribution of Dengue cases based on medical record data and produce a geographic distribution map to support Dengue control efforts at the Puskesmas level. This study used a quantitative descriptive design with secondary data from medical records at Karangsari Health Center. The sample consisted of 255 DHF patients in 2025, selected using a total sampling technique. Data were processed through editing, geocoding patient addresses, and spatial analysis using QGIS software.The results showed 255 Dengue  cases in 2025 with fluctuating monthly trends, peaking in April and lowest in December. Case distribution was uneven and tended to cluster. High-risk areas accounted for 15.7%–21.2%, moderate-risk areas 9.8%–15.7%, and low-risk areas 7.1%–9.8%. Megu Cilik Village had the highest proportion of cases, while other villages were categorized as moderate and low risk. This pattern indicates that Dengue incidence is influenced by environmental conditions, vector density, host factors, rainfall, and Aedes aegypti presence. GIS provides clearer spatial visualization, helping identify high-risk areas and supporting targeted public health interventions.

Health-related SMEs in Indonesia have significant opportunities to enter international markets, but many businesses still face limitations in digital capabilities, innovation, and readiness for external markets. This study aims to examine the influence of digital transformation on the success of health-related SMEs in going international, both directly and through business innovation as a mediator. The study employs a quantitative approach using a cross-sectional survey design involving 200 owners or key managers of SMEs in East Java, selected via purposive sampling. Data were analysed using Structural Equation Modelling-Partial Least Squares (SEM-PLS). The results indicate that digital transformation has a positive influence on business innovation and the success of going international. Business innovation also has a positive effect on internationalisation success and mediates the relationship between digital transformation and external market success. These findings confirm that digitalisation should not merely be understood as an operational tool, but as a strategic capability that must be integrated with product, process, marketing, and business model innovation. The research implications emphasise the importance of strengthening digital capabilities and business innovation to enhance the global competitiveness of Indonesian health-related SMEs

The coffee shop industry in Indonesia is experiencing rapid growth that requires business owners to optimize data-driven strategies. This study aims to analyze customer preferences at Semanis Coffee and Resto using data mining methods  to support more effective business decision-making. The method used is Market Basket Analysis with the FP-Growth algorithm for association rule mining and the K-Means algorithm for customer segmentation. The research data consists of 672 sales transactions during the March-May 2025 period. The results of the association analysis with a minimum support of 0.004 and a minimum confidence of 0.2 resulted in five valid rules with a lift ratio above 1. The strongest rule is the combination of Americano→Milk Choco with a confidence of 42.9% and an elevator ratio of 5.229, indicating a strong linkage between products. The most popular products are Milk Choco (10.8%) and Americano (8.5%). Customer segmentation analysis identified three clusters: Cluster 0 (Loyal Customers) 80% with high frequency but low transaction value; Cluster 1 (Occasional Customers) 10% with low activity; and Cluster 2 (Large Buyers) 10% with high transaction value but low frequency. This study concludes that product bundling strategies, loyalty programs, reactivation campaigns, and premium services can be applied to increase the effectiveness of coffee shop businesses.

This study aims to explore the trends in the development of scientific publications on beauty privilege, focusing on the growth in the number of articles, citation trends, as well as keyword mapping and the dominant themes emerging in the literature. The method used is a literature review with a descriptive bibliometric approach, referring to the PRISMA model which includes four stages: identification, screening, eligibility, and inclusion. Data were collected from Google Scholar using the Publish or Perish (PoP) software, with the keyword “beauty privilege.” The analysis results show that the number of publications has increased significantly since 2021, peaking in 2023 and 2024. In terms of citations, 2023 is the most influential year, having the highest number of citations. Keyword analysis using VOSviewer generated seven topic clusters, with dominant keywords such as beauty privilege, body shaming, and social media. The conclusion of this study indicates that the topic of beauty privilege is becoming increasingly relevant and evolving, opening opportunities for further research from various social, cultural, and psychological perspectives.

This study aims to examine user opinion tendencies toward Gojek services by integrating Random Forest and K-Means Clustering approaches. The dataset consists of 15,000 user reviews collected throughout 2025 using web scraping techniques. The initial stage focuses on data preprocessing, including text cleaning, case normalization, tokenization, removal of non-informative stop words, and lemmatization to restore words to their base forms. Subsequently, sentiment labels are assigned using a lexicon-based approach. The next phase involves classification modeling through Random Forest to identify sentiment tendencies, while K-Means Clustering is employed to uncover latent patterns within the opinion data. The findings indicate that the Random Forest model achieves an accuracy level of 0.878, demonstrating strong performance in distinguishing positive and negative sentiments, as reflected by f1-scores of 0.932 and 0.818, respectively. However, the model shows limitations in consistently identifying neutral sentiment. In contrast, the implementation of K-Means Clustering successfully categorizes the data into three primary clusters, providing a more structured representation of user opinion characteristics. Overall, these results offer empirical insights that can serve as a strategic reference for enhancing the quality of Gojek’s service delivery.

Background: Work stress is one of the most significant issues faced by healthcare professionals, particularly among nurses. Resilience can help individuals mitigate the negative impacts of working in high-pressure environments. A resilient person is able to manage stress and emotions effectively. Objective: The aim of this study is to examine the relationship between resilience and work stress among nurses at RSUD Dr. Soegiri Lamongan. Methods: The research employed a cross-sectional approach, with a sample of 135 nurses selected using cluster random sampling. Data was collected using a questionnaire instrument. Result: The study results indicated that the majority (74.8%) of nurses had a moderate level of resilience, while most (52.6%) experienced mild work stress. Based on Spearman’s Rho test analysis, the study found a p-value of 0.000 (p<0.05) and a correlation coefficient (r?) of -0.500, leading to the acceptance of H1, which confirmed a relationship between resilience and work stress among nurses at RSUD Dr. Soegiri Lamongan. Conclusion: Nurses who have a high level of resilience have low work stress because the level of resilience that each individual has can reflect their ability to maintain balance when life is unstable. .

This study aims to explore the meaning of service excellence from the perspective of hotel employees at Kinasih Resort Depok, Indonesia. Most existing research on service excellence has focused on guest satisfaction, leaving the subjective experiences of employees as service providers underexplored. This study employs a qualitative approach with a descriptive phenomenological design. Data were collected through in-depth interviews, participatory observation, and documentation from five purposively selected informants across the F&B Service, Housekeeping, Front Office, Human Resources, and management departments. Data analysis followed Moustakas's phenomenological procedure encompassing epoché, horizonalization, theme clustering, and essence description. Findings reveal that employees construct layered meanings of service excellence according to their hierarchical positions: frontline workers emphasize friendliness and responsiveness, supervisors emphasize speed and problem resolution, while management frames it as a holistic service ethos encompassing internal relationships. Emotional labor emerged as an inevitable dimension managed through collaboration, prioritization, and de-escalation strategies. Organizational factors including training systems, communicative leadership, guest feedback-based evaluation, and managerial attention to employee well-being demonstrably shape how employees internalize service excellence values. This study contributes to employee-centered literature on service excellence and offers practical implications for human resource development in resort contexts.

Individual behavioral factors are critical determinants of organizational effectiveness and a vital component of modern organizational diagnosis. This study aims to identify and map individual behavioral factors as strategic indicators in organizational diagnosis using a Systematic Literature Review (SLR) approach guided by PRISMA 2020. Analysis of ten selected articles reveals that organizational effectiveness in the digital transformation era is driven by a reciprocal equilibrium between an individual's cognitive infrastructure and volatile work environment demands. The findings synthesize these behaviors into four strategic clusters: psychological well-being as primary infrastructure, digital structural support audits, justice and trust equilibrium, and psychological contract synchronization. This research provides tactical implications for Human Capital practitioners to transform annual diagnostic methodologies toward the implementation of monthly pulse surveys to detect fluctuations in well-being and disengagement intentions in real-time. This predictive diagnostic step is essential to mitigate turnover risks and design precise institutional interventions in hybrid work ecosystems.

Background: Work-life balance is an essential issue for all employees, especially nurses and healthcare organizations. Nurses face high role demands, particularly female nurses, who must juggle multiple responsibilities simultaneously, often leading to an imbalance in their personal lives. Objective: The aim of this study is to examine the relationship between social support and work-life balance among female nurses in hospitals. Results: This correlational study used a cross-sectional approach. The sample consisted of 92 female nurses selected through cluster random sampling. Data was collected using a questionnaire and analyzed using the Spearman’s Rho test. The study results indicated that the majority (70.7%) of female nurses experience low social support, and most (68.5%) also had poor work-life balance. Based on the ordinal scale analysis using the Spearman’s Rho test, the study found a p-value of 0.000 (p<0.05) and a correlation coefficient (r?) of -0.610, leading to the acceptance of H1. This confirms a significant relationship between social support and work-life balance among female nurses in hospitals. Conclusion: It can be concluded that social attention and support are crucial for female nurses in carrying out their duties. With this support, female nurses can perform better and more effectively, and balance their work and personal lives.

Online games are one of the digital entertainment activities widely favored by adolescents; however, high-intensity use can lead to psychological impacts, one of which is anxiety. Anxiety in adolescents is characterized by feelings of restlessness, irritability, difficulty concentrating, and sleep disturbances, especially when they are unable to play online games or when they experience defeat in the game. This study aimed to determine the relationship between the intensity of online game use and the level of anxiety among adolescents. This study used a quantitative design with a cross-sectional approach, involving 113 respondents selected using a cluster sampling technique. The research instruments used were the DASS questionnaire and an online game usage intensity questionnaire, and the data were analyzed using univariate and bivariate analysis. The respondents in this study were adolescents from SMAN 1 Wanadadi, most of whom were 16 years old (49.6%) and predominantly female (61.9%). The intensity of online game use was mostly in the moderate category (55.8%), while the level of anxiety was mostly in the mild category (89.0%). The results showed that most respondents had a moderate level of online game usage intensity and a mild level of anxiety. Bivariate analysis indicated that there was no significant relationship between the intensity of online game use and the level of anxiety among adolescents, with a p-value of 0.425 and a contingency coefficient value of 0.076. Therefore, it can be concluded that there is no relationship between the intensity of online game use and the level of anxiety among adolescents.