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Employee affective commitment is a critical factor for workforce retention and service quality in healthcare organizations, particularly among nurses who represent the largest professional group in hospitals. Kemayoran X Hospital has experienced persistently high nurse turnover rates, indicating potential deficiencies in affective commitment. This study aimed to examine the influence of perceived organizational support and organizational justice on nurses’ affective commitment, with work engagement serving as an intervening variable. A quantitative cross-sectional design was employed, involving 125 staff nurses at Kemayoran X Hospital selected through purposive sampling. Data were collected using structured self-administered questionnaires distributed via Google Forms and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results demonstrated that perceived organizational support, organizational justice, and work engagement simultaneously exerted a significant effect on affective commitment. Furthermore, perceived organizational support and organizational justice showed significant positive effects on work engagement, which in turn significantly influenced affective commitment. Mediation analysis confirmed that work engagement partially mediated the relationships between perceived organizational support and affective commitment, as well as between organizational justice and affective commitment. These findings indicate that nurses who perceive fair treatment and strong organizational support are more likely to be engaged in their work and emotionally committed to their organization. In conclusion, strengthening organizational support systems, ensuring fairness in decision-making processes, and fostering work engagement are essential managerial strategies to enhance nurses’ affective commitment and reduce turnover in hospital settings.

Tambak Mother and Child Hospital experienced a 15% decline in patient visits in 2024, involving both new and returning patients. This decline highlights the importance of patient loyalty, as loyal patients are more likely to continue using hospital services and recommend the hospital to others. This study aims to examine the effects of social media marketing and patient experience on patient loyalty, with patient engagement as a mediating variable.This study employed a quantitative causal research design. Data were collected from 190 patients using purposive sampling. Partial Least Squares–Structural Equation Modeling (PLS-SEM) was used to analyze the relationships among variables.The results indicate that social media marketing, patient experience, and patient engagement simultaneously have a significant effect on patient loyalty. Individually, social media marketing, patient experience, and patient engagement each show a positive and significant influence on patient loyalty. In addition, social media marketing and patient experience positively affect patient engagement. The findings further confirm that patient engagement mediates the relationships between social media marketing and patient loyalty, as well as between patient experience and patient loyalty.These findings suggest that hospital management should strengthen interactive communication through social media platforms, particularly Instagram, improve service efficiency by increasing staffing levels, and enhance service quality through friendly staff behavior and faster service processes. Future research is recommended to include broader samples across Mother and Child Hospitals and incorporate additional variables such as patient satisfaction, service quality, and trust.

This study was carried out at RS Hj. Fatimah Sulhan in Kabupaten Demak, Jawa Tengah, which functioned as both the research site and the moderating context of the investigation. The research aims to examine how personal compensation, Organizational Citizenship Behavior (OCB), and organizational commitment influence employee work performance within the hospital environment. A quantitative research design was implemented, involving 150 employees selected as respondents through appropriate sampling procedures. Data were collected using structured questionnaires and subsequently analyzed using Structural Equation Modeling (SEM) with the AMOS software to test the hypothesized relationships among variables. The findings reveal that personal compensation, OCB, and organizational commitment each exert a positive and statistically significant impact on employee performance. These results indicate that fair and competitive compensation, strong voluntary work behaviors, and a high level of commitment to organizational goals collectively enhance productivity, service effectiveness, teamwork quality, and overall institutional performance in the healthcare setting.

This study investigates the influence of Apparatus Competency and Information Systems on Community Political Participation in the Local Government Head Election during the COVID-19 pandemic era in Karawang Regency. The COVID-19 pandemic has posed significant challenges to democratic processes, particularly in maintaining voter participation while ensuring public health safety. Employing a mixed-methods approach combining quantitative and qualitative data with Structural Equation Modeling (SEM) analysis, this research analyzed data from 263 respondents across various election administrative units. The results indicate that: (1) Apparatus Competency does not have a significant positive effect on Community Political Participation (T-value = 1.01 < 1.96); (2) Information Systems have a significant positive effect on Community Political Participation (T-value = 2.78 > 1.96; path coefficient = 0.67). The combined contribution of both variables explains 76% of the variance in political participation. From these findings, the study proposes the Skills Democracy Model, emphasizing that digital information skills and organizational experience are critical determinants of democratic participation quality during pandemic conditions. These findings have significant implications for election governance reform and e-democracy development in Indonesia.

This study investigates the optimization of claims under the Indonesian Case-Based Groups (INA-CBGs) payment mechanism within the National Health Insurance Program (Jaminan Kesehatan Nasional) at Hospital X in Serang. The research aims to analyze the influence of managerial competence, digital adoption, and organizational behavior on claim effectiveness, with policy implementation serving as a moderating variable. Employing a quantitative explanatory approach, data were collected from 144 respondents comprising management staff, casemix teams, and medical record officers through questionnaires and structured interviews. Structural Equation Modeling–Partial Least Square (SEM-PLS) was applied to examine the relationships among variables. Findings reveal that managerial competence, digital adoption, and organizational behavior significantly and positively affect the optimization of INA-CBGs claims. Furthermore, the implementation of the National Health Insurance Program policy strengthens these relationships, enhancing claim efficiency and equity. The results align with the Resource-Based View theory, highlighting the strategic role of internal resources in achieving organizational performance. Managerial implications include capacity building for managers, integration of hospital information systems (SIMRS) with e-Claim platforms, and fostering collaborative organizational culture. Overall, the study underscores the importance of managerial, technological, and behavioral factors, moderated by policy implementation, in improving hospital claim optimization under the INA-CBGs system.

Digital transformation in the management of state property is a necessary step towards achieving transparent and accountable governance. The Minstry of Finance, through the Directorate General of State Assets, has developed the State Asset Management Information System Version 2 application as a means of digital based management, but its implementation still faces challenges related to interest in its use by work unit operators. This study aims to evaluate the impact of intentions, attitudes, and subjective norms on interest in using the SIMAN V2 application at the Surabaya State Assets and Auction Service Office using the Theory of Reasoned Action (TRA) approach. Using a quantitative design through a survey, this study was conducted at the Surabaya KPKNL with subjects being SIMAN V2 application operators in work units in the working area. Data colection techniques used a questionnaire with a Likert scale. Data analysis was performed using Structural Equation Modeling (SEM) based on Partial Least Square (PLS) using SmartPLS software. The results of the study indicate that intention, attitude, and subjective norms have a positive and significant effect on interest in using the SIMAN V2 application. This study shows that psychological and social factors play an important role in supporting technology adoption in the public sector. The conclusion emphasizes that increased interest in use can be achieved by strengthening individual intentions, forming positive attitudes, and providing workplace support. Increased socialization, ongoing technical training, and recommendations for further research institutional supportfrom agencies to optimize the use of the SIMAN V2 application.

This study is motivated by the increasing need for accurate modeling and classification of one-dimensional signal data in intelligent systems. The rapid development of deep learning has led to the adoption of more adaptive and complex neural network architectures capable of capturing both temporal dependencies and local patterns in sequential data. This research aims to analyze and compare the performance of several deep learning models, namely Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid Convolutional Neural Network–GRU (CNN–GRU) model for signal data classification. The research method employs a quantitative experimental approach involving data preprocessing, windowing, model training, and performance evaluation. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the hybrid CNN–GRU model outperforms the other models, particularly in capturing local features and long-term temporal dependencies within signal data. These findings suggest that the integration of convolutional layers and recurrent mechanisms enhances feature representation and learning stability. This study is expected to contribute both theoretically and practically to the development of deep learning models for signal processing and time-series-based intelligent applications.

In the rapidly evolving digital economy, the ability to anticipate transaction surges is a strategic asset for marketplace platforms to maintain operational efficiency. This research aims to build an accurate daily transaction volume forecasting system thru the implementation of an Extract, Transform, and Load (ETL) pipeline and Autoregressive Integrated Moving Average (ARIMA) predictive modeling. The dataset used is sourced from dataset_olshop.csv, which includes transaction history for the entire year of 2025. The ETL stage focused on data cleaning and handling missing values, while time series analysis began with the Augmented Dickey-Fuller (ADF) stationarity test, which yielded a significant p-value of 0.000006. The parameter model was optimized using the auto_arima algorithm, which determined the ARIMA(2,0,0) configuration as the best model. The evaluation results of the model show fairly stable performance with a Root Mean Squared Error (RMSE) value of 2.002 and a Mean Absolute Error (MAE) of 1.704 on the test data. Research findings reveal a consistently higher purchasing pattern during the mid-month and end-of-month periods, with an average of 5.52 daily transactions, compared to the beginning of the month, which saw 5.48 transactions. The 30-day forecast results provide valuable insights for online store managers to proactively adjust inventory and logistics workforce allocation strategies. This research concludes that integrating data engineering techniques and statistical analysis can provide predictive solutions for the dynamics of the digital market.

The moral crisis and the decline in students' social awareness encourage education to focus not only on academics but also on character development. The internalization of social education values is important for fostering empathy, responsibility, and social sensitivity. At SMPN 1 Kunjang, undisciplined behavior and low levels of social concern indicate the need for a more effective internalization strategy. This study aims to explore the process of internalizing social education values and the supporting and inhibiting factors among seventh-grade students at SMPN 1 Kunjang. The research method used is a descriptive qualitative approach, with the research location at SMPN 1 Kunjang. Data were collected through observation, interviews, and documentation. The results show that the internalization of social education values at SMPN 1 Kunjang is carried out through habituation, role modeling, school rules, and routine activities that cultivate students' empathy and responsibility. Supporting factors include teacher role modeling, routine school programs, and a culture of discipline. Meanwhile, inhibiting factors include weak family roles, negative peer influence, and lack of discipline.

RS at Kemayoran continues to experience low conversion of antenatal care (ANC) patients to delivery services, with a conversion rate of 6.9% in 2024. The maternity ward Bed Occupancy Rate (BOR) also remains below national standards. Preliminary assessments indicate dissatisfaction with the hospital’s healthscape, low mimetic desire reflected in limited recommendations, and suboptimal perceived value. This study examines the effects of healthscape and mimetic desire on childbirth location decisions, with perceived value tested as a mediating variable.Methods: A quantitative cross-sectional study was conducted using Structural Equation Modeling (SEM). Data were collected from 210 ANC patients at RSUD Kemayoran through structured questionnaires. Variables included healthscape, mimetic desire, perceived value, and delivery location decision. All instruments met validity and reliability criteria.Results: Healthscape and mimetic desire significantly influenced the decision to choose RSUD Kemayoran for childbirth. Healthscape did not significantly affect perceived value, whereas mimetic desire showed a significant effect. Perceived value had a significant direct effect on delivery decisions but did not mediate the relationships between healthscape or mimetic desire and delivery choice. Healthscape emerged as the most influential determinant.Conclusion: Physical healthcare environments play a critical role in childbirth location decisions. Improving healthscape quality and strengthening professional and social recommendations may enhance ANC-to-delivery conversion rates in public hospitals.

The phenomenon of religion-based radicalism remains a serious threat to the sustainability of national and state life, including within educational institutions. Educational institutions hold a strategic role in instilling religious values that are peaceful, tolerant, and civilized. Therefore, religious moderation education has become a vital approach as a preventive measure against radical ideologies. This study aims to examine the role and urgency of religious moderation education as a shield against radicalism in educational institutions. The research method employed is a literature study, analyzing various literatures such as books, scientific articles, and policy documents related to religious moderation and character education. The results show that religious moderation education can instill the values of tawassuth (moderation), tasamuh (tolerance), tawazun (balance), and i‘tidal (justice) in students. These values contribute significantly to forming religious attitudes that are inclusive, humanistic, and non-violent. The implementation of religious moderation education in educational institutions can be achieved through curriculum integration, educator role-modeling, the cultivation of school culture, and the strengthening of contextual religious literacy. Thus, religious moderation education plays a crucial role as an ideological and moral fortress in preventing the entry and growth of radicalism within the educational environment.

This study aims to analyze the effect of social media advertising exposure and digital financial literacy on consumptive behavior, with self-control as a mediating variable among 11th grade high school students in Kotabumi Selatan District. This quantitative study involved 267 respondents from five public and private high schools selected using proportional sampling techniques. Data were collected through structured questionnaires and analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results show that exposure to social media advertising has a significant positive effect on consumptive behavior, indicating that higher advertising exposure increases students’ tendency toward excessive consumption. However, advertising exposure does not have a significant effect on self-control. Digital financial literacy has a significant positive effect on self-control, but does not directly influence consumptive behavior. Furthermore, self-control has a significant negative effect on consumptive behavior and plays a mediating role in the relationship between digital financial literacy and consumptive behavior. These findings confirm that strengthening digital financial literacy is crucial for improving adolescents’ self-control and reducing consumptive behavior in the digital era.

This study is grounded in the issue of low student discipline and learning motivation in elementary schools, which requires teachers to apply more effective and context-based instructional strategies. The purpose of this research is to describe how teachers utilize social learning theory to enhance students’ discipline and motivation, as well as to analyze the impact of these strategies on classroom behavior and student engagement. This research employed a descriptive qualitative approach, with data collected through observations, interviews, and documentation involving teachers and students. The findings show that teacher strategies integrating modeling, positive reinforcement, and collaborative learning successfully create a more conducive learning environment. The use of teacher and peer role models was found to increase compliance with classroom rules, while the provision of positive feedback encouraged students to participate more enthusiastically in learning activities. Moreover, socially interactive learning helped students develop confidence and active engagement. The implications of this study affirm that social learning theory can serve as a strong foundation for teachers to design strategies that promote positive behavior and intrinsic motivation, making it highly relevant for integration into daily classroom practice.

The rapid development of generative Artificial Intelligence (AI) technology offers significant efficiency opportunities across various sectors; however, empirical research within the local Indonesian context, particularly in Batam City, remains scarce. This exploratory study aims to analyze the influence of positive perception, negative perception, and AI regulation understanding on technology adoption trends, as well as productivity and product innovation opportunities among creative industry players. The creative industry is a focal point due to the inherent tension between technological efficiency and the preservation of human originality in the creative process. This research employs a quantitative causal approach, utilizing a sample of 30 respondents reached through snowball sampling techniques. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The findings reveal that only positive perception has a significant direct impact on product innovation (p=0.004), while AI regulation and technical adoption do not show significant effects. This suggests that a positive technology mindset is a more decisive factor for innovation than technical mastery or current regulatory compliance. These results underscore the urgent need for local government socialization of AI policies and enhanced digital literacy for Batam's creative practitioners to transform them from mere users into strategic AI-driven innovators.

Instagram has become a strategic medium for government institutions in delivering public information, particularly weather and disaster-related information that requires speed, clarity, and ease of understanding. The BMKG of Gowa Regency utilizes digital communication innovations through the use of informative memes and a virtual character named Shinna as a visual communication strategy to enhance the effectiveness of information dissemination to the public. This study aims to analyze the influence of meme usage and the virtual character Shinna on the information satisfaction of Instagram users of BMKG Gowa Regency by employing the Stimulus–Response (S–R) theory perspective, which views visual messages as stimuli capable of eliciting cognitive and affective responses from audiences. This research adopts a quantitative approach using a survey method. Data were collected through an online questionnaire with a four-point Likert scale administered to followers of the BMKG Gowa Regency Instagram account who had viewed or interacted with meme content and the virtual character Shinna. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS software. The results indicate that the use of memes and the virtual character Shinna has a positive and significant effect on users’ information satisfaction, both partially and simultaneously. Meme usage shows a more dominant influence compared to the virtual character Shinna, while the coefficient of determination (R²) value of 0.834 indicates that both variables explain 83.4% of the variance in users’ information satisfaction. These findings confirm that public communication strategies based on memes and virtual characters are effective in enhancing audience understanding, comfort, and satisfaction with disaster-related information.

Penelitian ini bertujuan untuk menganalisis pengaruh knowledge sharing dan pemberdayaan pegawai terhadap kinerja pegawai melalui kepuasan kerja sebagai variabel intervening pegawai di Dinas Pemberdayaan Perempuan, Perlindungan Anak, Pengendalian Penduduk dan Keluarga Berencana Kabupaten Pekalongan. Populasi yang digunakan dalam penelitian ini adalah seluruh pegawai di Dinas Pemberdayaan Perempuan, Perlindungan Anak, Pengendalian Penduduk dan Keluarga Berencana Kabupaten Pekalongan yang berjumlah 105 orang. Jumlah sampel yang digunakan adalah 84 orang yang dipilih dengan Slovin secara proporsional random sampling. Teknik analisis data yang digunakan adalah Structural Equation Modeling-Partial Least Square (SEM-PLS). Hasil penelitian menunjukkan bahwa knowledge sharing dan pemberdayaan pegawai berpengaruh positif dan signifikan terhadap kepuasan kerja dan kinerja pegawai. Kepuasan kerja juga berpengaruh signifikan terhadap kinerja pegawai. Hasil penelitian juga menunjukkan bahwa kepuasan kerja memiliki peran mediasi dalam memediasi knowledge sharing dan pemberdayan pegawai terhadap kinerja pegawai.

Penelitian ini dilatarbelakangi oleh pentingnya peningkatan kinerja pegawai sektor publik yang sering terkendala birokrasi, budaya organisasi hierarkis, dan regulasi ketat. Kepemimpinan autentik dan penyesuaian pekerjaan dipandang sebagai faktor yang dapat   memengaruhi kinerja pegawai baik secara langsung maupun melalui keterlibatan kerja. Kepemimpinan autentik berperan dalam menciptakan iklim kerja yang terbuka dan penuh integritas, sedangkan penyesuaian pekerjaan memberi ruang bagi pegawai menyesuaikan pekerjaan dengan kekuatan dan preferensi pribadi. Penelitian ini menggunakan metode kuantitatif dengan survei terhadap 153 pegawai Dinas Perhubungan Kabupaten Pemalang. Instrumen berupa kuesioner berskala Likert yang diuji validitas dan reliabilitasnya. Analisis data dilakukan dengan Partial Least Squares Structural Equation Modeling (PLS-SEM) untuk menguji hubungan langsung maupun mediasi antar variabel berdasarkan teori JD-R, COR, dan Authentic Leadership. Hasil penelitian menunjukkan empat hipotesis diterima dan satu ditolak. Penyesuaian pekerjaan berpengaruh positif dan signifikan terhadap keterlibatan kerja dan kinerja pegawai, serta menjadi prediktor paling kuat bagi kinerja (β = 0,432). Kepemimpinan autentik berpengaruh positif terhadap keterlibatan kerja (β = 0,335), namun tidak signifikan terhadap kinerja (β = 0,120). Keterlibatan kerja terbukti memediasi sebagian hubungan penyesuaian pekerjaan dengan kinerja, tetapi tidak memediasi pengaruh kepemimpinan autentik. Model penelitian mampu menjelaskan 44,2% varians keterlibatan kerja dan 60,8% varians kinerja pegawai. Temuan ini menegaskan pentingnya faktor individual seperti penyesuaian pekerjaan dibandingkan faktor kepemimpinan top-down dalam meningkatkan kinerja pegawai di sektor publik. Implikasi praktis penelitian ini adalah perlunya organisasi pemerintah mengembangkan program penyesuaian pekerjaan, memperkuat keterlibatan kerja, serta membangun kepemimpinan autentik sebagai fondasi budaya kerja yang positif.

The formation of Christian character in church-based education often faces challenges when disciplinary approaches rely heavily on punishment and external compliance. This article examines the relevance of behaviorism in shaping Christian character through the lens of positive discipline an approach that emphasizes reinforcement of desirable behavior, nurturing relationships, and the development of intrinsic moral awareness. Using a literature review and a small scale case analysis of contemporary church educational practices, this study evaluates how the principles of reinforcement, modeling, and behavioral consistency can be integrated with Christian values such as love, repentance, and the cultivation of conscience. The findings indicate that behaviorism remains useful when applied selectively within a holistic Christian educational theology. Positive discipline aligns more closely with biblical values because it promotes responsible character growth rather than mere obedience. This article contributes to the pedagogical discourse of church education by proposing an integrative framework that combines behavioristic principles with positive discipline to enhance effective and sustainable Christian character formation.

This study aims to analyze the role of spiritual leadership of the kiai in strengthening the organizational resilience of Al-Asy’ary Islamic Boarding School in the era of Society 5.0. The research employs a qualitative approach with a case study design. Data were collected through in-depth interviews with the kiai, teachers, and students, as well as observation and supporting documentation. Data analysis followed the interactive model of Miles, Huberman, and Saldaña, consisting of data condensation, data display, and conclusion drawing. The findings indicate that the kiai’s spiritual leadership is a key determinant of pesantren resilience through the integration of transcendental, ethical-humanistic, and adaptive-progressive dimensions. The kiai successfully guides the selective and meaningful use of digital technology by positioning it as a means of service (khadam), rather than an end in itself. Leadership practices based on role modeling, moral values, and spiritual reinforcement foster students’ moral autonomy and create a stable organizational climate amid digital disruption. This study concludes that the resilience of traditional pesantren in the Society 5.0 era lies in the strength of spiritual values sustained through adaptive and continuous spiritual leadership.

Graph theory as a branch of discrete mathematics has experienced significant development in its application to modern complex network systems, particularly in digital social networks and transportation systems. This research aims to analyze fundamental concepts of graph theory, examine characteristics of cycle detection algorithms along with their computational complexity, investigate their application in digital social network analysis, and explore their implementation in digital transportation system optimization. The research method employs a qualitative approach with library research focusing on scientific literature from 2020-2025 period from accredited academic databases such as Scopus, Web of Science, and IEEE Xplore, utilizing thematic analysis techniques to identify meaningful patterns from the examined literature. Research findings indicate that fundamental graph theory concepts including vertices, edges, and graph classifications form the foundation for relational structure modeling. Cycle detection algorithms such as Depth-First Search, Union-Find, and Tarjan demonstrate effectiveness with O(V+E) complexity for large-scale graphs. Applications in digital social networks facilitate community identification through Multi-View Clustering, centrality analysis for influencer detection, and understanding viral information dissemination patterns. Implementation in digital transportation systems demonstrates route planning optimization using Dijkstra and Bellman-Ford algorithms, vulnerability analysis through articulation point and bridge identification, and bottleneck detection with betweenness centrality. The research concludes that integration of graph theory in discrete mathematics education enhances critical thinking skills and real-world application understanding, with recommendations for algorithm development for massive dynamic graphs and machine learning integration in graph algorithm optimization.