Publication Search

This study aims to analyze the novel Laskar Pelangi by Andrea Hirata using a critical hermeneutic approach developed by Jürgen Habermas. The focus of this research is to uncover the critical meaning contained in the novel as a reflection of social reality, especially in the field of education. The method used is descriptive qualitative research with data collection techniques through literature studies and text analysis in the form of excerpts in novels. The results of the study show that the novel Laskar Pelangi not only presents an inspiring story, but also contains criticism of the education system in Indonesia which is still colored by inequality and injustice. In the aspect of communicative action, it was found that there was a dialogical interaction between teachers and students as well as the value of solidarity and strong struggle. However, in the aspect of communication distortion, there is injustice in access to education and a lack of space for poor groups to voice their interests. In addition, the analysis also reveals the existence of ideology and domination, especially economic dominance over education and social systems that oppress the lower groups. On the other hand, the emancipatory interest in this novel is reflected through education as a tool of liberation and the struggle of its characters in fighting against limitations. Thus, this study concludes that the novel Laskar Pelangi has an important role as a social criticism medium that is able to build readers' critical awareness of the reality of education and social inequality that occurs in society.

Public service quality has emerged as a crucial metric for assessing how well the government functions and the efficiency of its administration. Recently, rising expectations from the public have led gov-ernments to offer services that are open, responsible, effective, and attuned to citizens' needs. Alongside administrative changes and the evolution of governance models focused on efficiency and citizen satisfaction, the appetite for high-quality public services has surged. Nonetheless, numerous public entities continue to struggle with providing reliable and top-notch services due to a lack of defined service norms and systems for measuring performance. The purpose of this research is to investigate ways to enhance public service quality by establishing robust service standards and quantifiable performance metrics. The study employs a qualitative descriptive methodology, drawing on a review of relevant lit-erature from the past seven years. Multiple academic sources were analyzed to uncover essential ideas, frameworks, and empirical evidence concerning public service management, the enhancement of service quality, and the assessment of performance in governmental organizations. The results show that adopting well-defined service standards, along with measurable performance metrics, can greatly en-hance service effectiveness, accountability, and overall public satisfaction. Additionally, merging prin-ciples of service excellence with quantifiable indicators promotes transparency, boosts organizational performance, and fosters ongoing improvements in service delivery. The research concludes that to enhance public service quality, a structured framework for service standards, ongoing performance assessments, and a firm organizational dedication to innovation and service enhancement are necessary.

This study aims to analyze the impact of inflation on the profitability of Micro, Small, and Medium Enterprises (MSMEs) operating in traditional markets. Inflation influences key business aspects, including rising production costs, declining consumer purchasing power, and instability in input prices, all of which can disrupt business performance. The research employed a quantitative approach using survey data collected from MSME actors to assess these effects. The findings reveal that inflation has a significant negative impact on MSME profitability, particularly through the reduction of profit margins. This occurs as businesses face higher raw material costs while simultaneously experiencing a decline in sales volume due to weakened consumer demand. As a result, many MSMEs struggle to maintain financial stability and sustain their operations under inflationary pressure. These findings highlight the need for adaptive strategies among MSMEs, such as cost efficiency and pricing adjustments. Additionally, the study offers important policy implications for the government to support MSMEs through targeted interventions, including price stabilization measures and financial assistance programs, in order to maintain business resilience and economic sustainability.

International student enrollment is a critical driver of financial sustainability for Higher Education Institutions (HEIs). While advanced forecasting is standard in the corporate sector, its application in educational planning remains limited. This study addresses this gap by comparing the predictive performance of ARIMA, Facebook Prophet, and Long Short-Term Memory (LSTM) models. Using a publicly available annual dataset from a US-based institution (2000–2022), the analysis employed a strategic partition training on 2000–2017 and testing on 2018–2019 to validate models on stable, pre-pandemic data. Empirical results revealed that the statistical ARIMA (2,1,0) model demonstrated superior accuracy, achieving a Mean Absolute Percentage Error (MAPE) of 1.26%. Conversely, Prophet (11.81%) and LSTM (13.84%) struggled with the limited sample size, failing to generalize effectively compared to the linear approach. The findings suggest that for annual enrollment trends, parsimonious statistical models outperform complex deep learning architectures, providing administrators with a robust, accessible framework for data-driven strategic decision-making.

The increasing complexity and scale of modern network traffic driven by IoT and cloud-based infrastructures have made accurate intrusion detection a critical challenge. Conventional network intrusion detection systems (NIDS) and many deep learning–based approaches struggle to reliably detect minority and stealthy attacks due to severe class imbalance and limited discrimination of subtle traffic patterns. To address these limitations, this study proposes a hybrid CNN–RBF–Attention framework for network intrusion detection. The proposed model integrates three complementary components: (i) a convolutional neural network for hierarchical feature extraction from network flow data, (ii) a radial basis function (RBF) network for localized nonlinear classification using prototype-based decision regions, and (iii) an attention mechanism that adaptively weights RBF activations to emphasize discriminative traffic patterns. SMOTE is applied exclusively to the training data to mitigate class imbalance. The framework is evaluated on the widely used CICIDS2017 and CICIDS2018 benchmark datasets in both binary and multiclass settings, using recall, precision, F1-score, confusion matrices, and ROC analysis. Experimental results demonstrate that the proposed hybrid model consistently outperforms standalone CNN and RBF baselines, particularly in terms of recall and F1-score. On the CICIDS2018 dataset, the model achieves 99.81% accuracy and 99.81% F1-score in binary classification, and 99.54% accuracy and 99.54% F1-score in multiclass classification. On CICIDS2017, it achieves 98.12% accuracy and 98.12% F1-score in binary classification, and 98.92% accuracy and 98.92% F1-score in multiclass classification. Confusion matrix and ROC analyses further show strong class separability and reliable performance in low–false-positive-rate regions, which is critical for real-world IDS deployment. These results confirm that combining deep hierarchical feature learning, localized prototype-based classification, and attention-guided refinement yields a robust, operationally reliable intrusion detection framework for highly imbalanced network environments.

This article examines the theological thought of Saint Cyprian of Carthage, one of the third-century Church Fathers, within the context of the Church’s situation in his time, which was marked by profound struggles of faith, particularly the experience of persecution. The focus of the discussion is directed toward the historical and pastoral conditions that shaped Cyprian’s views on the unity of the Church, episcopal authority, and the validity of the sacrament of baptism. Accordingly, this article raises several key questions: What historical background formed Cyprian’s thinking on these three concepts? What were the central ideas he developed regarding ecclesial unity, episcopal authority, and baptism? And how are his ideas relevant to the Church’s teaching, especially in light of the Second Vatican Council? Using a historical and hermeneutical approach, this article traces Cyprian’s life background as well as his pastoral-theological responses to the concrete situations faced by Christians in his time. In the context of the post-persecution crisis, Cyprian played a significant role in addressing internal divisions within the Church, particularly debates concerning the readmission of the lapsi (those who had apostatized). From these struggles, it becomes evident how Cyprian firmly articulated the role of bishops as successors of the apostles and emphasized the sacrament of baptism as the legitimate gateway into ecclesial communion. Based on the historical background of Cyprian’s thought and these three central themes, the article then examines the contribution of Cyprian’s theology to the teachings of the Church as formulated in the Second Vatican Council. Thus, Cyprian’s thought is understood not only as a foundation of early ecclesiology, but also as a living source of faith reflection that remains relevant for the contemporary Church in responding to the dynamics and challenges of the modern age Keywords: Cyprian of Carthage, ecclesiology, unity of the Church, episcopal authority, sacrament of baptism, Second Vatican Council.

This study examines the economic dynamics experienced by migrant women through the perspective of abstract painting as a medium for personal and social reflection. The study uses a qualitative method with an artistic research approach, which departs from the researcher's personal experience as a migrant woman facing increasingly complex economic realities. The rising cost of living, financial constraints, and intertwined academic demands create pressure not only on material aspects, but also on psychological, emotional, and mental conditions. This situation demands adaptation strategies, resilience, and the ability to survive in the face of uncertainty in migrant areas. The dynamics of these experiences are then translated into visual language through an abstract expressionist approach utilizing mixed media techniques. Dynamic line elements, contrasting colors, bubble textures, and layers of material are used as symbols of the tension, struggle, and economic instability experienced by the subjects. The research findings show that abstract painting functions not only as a means of personal expression, but also as a medium for social reflection that records and articulates the experiences of migrant women who are often marginalized. This research contributes to the enrichment of contemporary art discourse, particularly in presenting visual narratives that voice economic issues and women's life experiences in a critical and reflective manner.    

This study explores the integration of deep learning based approaches in real time video content analysis for intelligent human computer interaction (HCI) in multimedia systems. Traditional video analysis techniques, such as rule-based methods and offline processing, struggle with real time performance and adaptability to complex video data. In contrast, the deep learning model used in this research, particularly Convolutional Neural Networks (CNNs), provides high accuracy in object detection, feature extraction, and real time processing. The integration of CNNs with interactive visualization modules enables dynamic adjustments to video content based on user interactions, ensuring a seamless and engaging user experience. The system was benchmarked in terms of its processing speed, accuracy, and responsiveness, showing significant improvements over traditional approaches in real time video analysis. Moreover, the study demonstrates that combining deep learning with real time visualization enhances the efficiency of interactive multimedia applications, making it suitable for dynamic environments such as surveillance, security monitoring, and interactive media. Despite the system's strong performance, challenges such as computational demands in high-resolution video processing were identified, highlighting the need for further optimization. Future work will focus on optimizing the system for different hardware platforms, incorporating multimodal inputs, and refining deep learning models to address computational bottlenecks. This research contributes to advancing HCI by providing insights into the integration of deep learning for real time video content analysis, which is pivotal for enhancing the interactivity and adaptability of intelligent multimedia systems.

Concept drift, the phenomenon where the statistical properties of data streams change over time, poses a significant challenge in machine learning, particularly for long term data streams. Traditional machine learning models, including batch learning and non-adaptive approaches, struggle to detect and adapt to these changes, leading to degraded performance and inaccurate predictions. This study proposes an adaptive computational model designed to detect and respond to concept drift using incremental learning techniques and statistical drift detection mechanisms. The model integrates an Adaptive Drift Detector (ADD) and Incremental Learning System, enabling real-time adjustments to data distribution changes. The model is evaluated across synthetic and real-world datasets, demonstrating its superior ability to detect abrupt, gradual, and recurring drifts compared to traditional models. Experimental results indicate that the adaptive model maintains high prediction accuracy, minimizes false positive rates, and reduces detection delays. Furthermore, the model performs well in resource-constrained environments, making it suitable for real-time applications such as healthcare prediction, fault detection, and IoT systems. Despite its promising performance, the study identifies challenges related to computational complexity and the model’s performance with imbalanced datasets and noisy data. Future research should focus on optimizing the model’s scalability, computational efficiency, and adaptability to more complex data types to ensure broader applicability in dynamic environments. This work contributes to advancing the detection and adaptation of concept drift, offering a robust solution for dynamic and evolving data streams.

The increasing complexity and scale of modern cybersecurity threats necessitate the development of advanced systems capable of efficiently detecting, analyzing, and mitigating incidents in real time. This paper proposes an automated framework for digital forensics and incident response that leverages big data analytics and real time network traffic profiling. The framework integrates cutting-edge technologies, including Apache Spark for real time data processing and Hadoop for scalable data storage, combined with machine learning models like LSTM and Autoencoders to detect anomalies and threats in network traffic. By automating the process of incident detection and response, this framework significantly reduces the time required to identify threats and improves the accuracy of forensic evidence correlation across heterogeneous network environments. The study highlights the advantages of using machine learning models and big data tools to address the limitations of traditional manual and semi-automated systems, which often struggle to keep pace with large-scale data generation. Testing results demonstrate that the proposed framework can handle large data volumes efficiently, providing real time, actionable insights with significantly reduced response times. Additionally, the framework improves forensic analysis by enabling the correlation of evidence from different devices and protocols, making it more effective than traditional methods in identifying the root cause of security incidents. However, challenges related to data heterogeneity, scalability, and system integration were encountered during testing. The proposed framework holds promise for significantly enhancing the efficiency and effectiveness of cybersecurity operations, with future work focusing on further integration of advanced AI techniques and machine learning models for dynamic and adaptive incident response.

This study investigates the role of Information Technology (IT) governance in enhancing risk management performance and ensuring regulatory compliance within multinational digital enterprises. As digital transformation continues to reshape the global business landscape, organizations face increasing challenges in managing technological risks and complying with complex regulatory requirements across various jurisdictions. The study adopts a quantitative approach, using a survey methodology to collect data from senior IT and compliance managers in multinational digital enterprises. The survey focuses on how IT governance frameworks, such as COBIT 2019 and ISO 27000, are utilized to align IT strategies with business objectives, mitigate risks, and maintain regulatory compliance. The findings indicate that organizations with well-established IT governance structures are better positioned to proactively identify and mitigate risks, ensuring greater consistency in meeting regulatory requirements. These organizations demonstrate improved risk management effectiveness, especially concerning cybersecurity, data privacy, and compliance with global regulations like GDPR. In contrast, organizations with ad hoc or decentralized governance structures struggle with fragmented risk management and compliance efforts. The study further highlights the importance of integrating IT governance frameworks with internal audit functions, specifically the Chief Audit Executive (CAE), to enhance cybersecurity resilience and ensure compliance with global standards. This research contributes to the literature by providing empirical evidence on the integration of IT governance, risk management, and regulatory compliance in multinational enterprises. It also highlights the need for a structured and systematic approach to IT governance to improve organizational performance in managing risks and ensuring consistent regulatory adherence. The study offers practical insights for organizations looking to optimize their IT governance structures in the face of rapid digital transformation.

Digital transformation (DT) has become a critical component for organizations aiming to enhance their operational efficiency, innovation, and competitiveness. However, many organizations struggle to achieve successful digital transformation due to the misalignment between their Enterprise Information Systems (EIS) and organizational strategic goals. This research seeks to design and validate a model for aligning EIS with digital transformation strategies to improve organizational effectiveness. By adopting the Design Science Research (DSR) approach, this study develops a practical model that integrates strategic planning, process management methodologies, and emerging technologies to facilitate alignment between IT and business strategies. The research includes key steps such as requirement analysis, artifact design, expert validation, and case study evaluation to ensure the model's robustness and applicability across different organizational contexts. Findings indicate that the proposed model significantly improves strategic-system alignment, enhances decision-making consistency, and facilitates better integration between business and IT units. The model also addresses common challenges such as resistance to change, skill gaps, and misalignment, fostering a supportive culture for digital transformation. In comparison to existing descriptive frameworks, the proposed model is more structured, adaptable, and actionable, providing organizations with a clear framework to guide their digital transformation efforts. This research contributes to the growing body of knowledge on EIS alignment and offers practical insights for organizations seeking to achieve successful digital transformation. Future research could explore the model's application in various organizational settings and examine its impact on long-term organizational growth and innovation.

Youth and youth ministry plays a strategic role in shaping the faith, character, and spiritual maturity of the younger generation. This study aims to analyze the spiritual needs, struggles, and relevant Christian Religious Education (PAK) strategies for youth at GBI Pondok Daud. Using a descriptive qualitative approach, data were obtained through direct observation, interviews with instructors, facility observations, and documentation during worship services. The results indicate that youth are highly enthusiastic about attending worship services and are actively involved in various ministry sectors, such as music, multimedia, and ushering. However, they face several struggles, including academic pressure, the influence of social media, and instability in personal spiritual discipline. Primary spiritual needs include Christian character development, a deeper understanding of God's Word, a supportive community, and consistent spiritual guidance. The implemented PAK strategies, such as creative worship, small group discussions, mentoring, and the use of digital media, have proven effective in addressing the needs of youth. This study concludes that GBI Pondok Daud's youth ministry has been successful, but still needs to strengthen discipleship, improve spiritual discipline, and develop experiential learning activities.

This study investigates the impact of GeoGebra-assisted collaborative learning on students' understanding of function graphs. Function graphs are fundamental in mathematics education, yet many students struggle to grasp the relationships between variables, primarily due to traditional teaching methods that focus on procedural skills rather than conceptual understanding. To address this challenge, the study incorporates GeoGebra, a dynamic mathematics software, alongside collaborative learning strategies. The research utilizes a quasi-experimental design involving high school students who had previously struggled with function graphs. The results demonstrate that the experimental group, which engaged in GeoGebra-assisted collaborative learning, showed a significant improvement of 27% in their post-test scores, compared to just a 6% improvement in the control group using traditional methods. The study highlights the effectiveness of GeoGebra in fostering a deeper conceptual understanding of mathematical functions by enabling students to visualize and manipulate graphs interactively. Additionally, collaborative learning encouraged peer interaction, reinforcing the learning process and promoting better problem-solving skills. The findings suggest that combining interactive tools like GeoGebra with collaborative learning techniques can enhance students’ mathematical comprehension, leading to improved engagement and performance in mathematics education.

This study examines the implementation of Servant Leadership within GMIM Syalom Lelema and its influence on congregational attendance in worship fellowship. Rooted in the theological model of leadership exemplified by Jesus Christ, Servant Leadership emphasizes humility, empathy, presence, and service as core leadership values. Using a qualitative case-study approach, data were collected through observations, interviews, and documentation to understand the relational dynamics between church leaders and congregational participation. The findings reveal that the congregation highly values leaders—pastors, elders, and deacons—who demonstrate genuine care, pastoral presence, and willingness to serve. Acts of pastoral visitation, listening to members’ struggles, and showing humility significantly strengthen emotional and spiritual bonds within the community, resulting in higher attendance and engagement in various worship activities. Conversely, leaders who lack servant-like attitudes tend to receive weaker responses from the congregation, which negatively impacts their participation in worship. The study concludes that Servant Leadership is not merely a theological ideal but a practical necessity within the communal culture of GMIM Syalom Lelema. The model effectively fosters stronger relationships, increases congregational commitment, and enhances the vitality of church fellowship. Keywords: Servant Leadership, Pastoral Ministry, Worship Attendance, Ecclesial Leadership, GMIM Syalom Lelema.

This study examines the effectiveness of national legislative strategies in promoting corporate accountability for industrial pollution and social justice violations. It analyzes a comparative legal framework, focusing on laws, enforcement mechanisms, and corporate liability regimes in countries such as France, Germany, Norway, China, and Australia. The research evaluates how mandatory due diligence laws, judicial measures, and transparency mechanisms help hold corporations accountable for environmental impacts. It compares voluntary compliance models with mandatory legal frameworks, noting the limitations of voluntary agreements in driving substantial environmental changes. Findings show that countries with strong legal frameworks, like the EU and Australia, achieve higher corporate compliance and environmental performance, while voluntary measures struggle to produce meaningful results. The study emphasizes the need for stronger enforcement, higher penalties for violations, and enhanced public transparency. Additionally, it explores integrating environmental justice considerations, such as community participation and fair compensation, into national strategies. The study offers policy recommendations for improving corporate responsibility through better legislation, harmonizing laws across jurisdictions, and fostering collaboration among governments, corporations, and civil society. It also suggests future research directions, including examining the long-term impacts of environmental justice policies in different global contexts.

The production sector at both the district and city levels is crucial for fostering structural change and boosting economic growth in specific areas. Still, many regions struggle with issues such as linking supply chains, readiness for technology, quality of labor, and efficient policies. This research intends to examine the strategies of the manufacturing sector at the district and city levels to enhance regional competitiveness and promote sustainable economic growth. The study utilizes a descriptive qualitative method based on a review of literature from academic journals, policy papers, and official statistics related to manufacturing progress. Results reveal that several important factors strongly affect regional manufacturing growth. These include the connection of local supply chains, industry strategies focused on the market, the implementation of digital and smart manufacturing methods, innovation encouraged by educational institutions and organizations, and the influence of local governments in developing an effective industrial policy atmosphere. Furthermore, creating designated industrial areas and managing operations efficiently significantly helps attract investments and boost the manufacturing output of regions. The research concludes that a cohesive and tailored manufacturing strategy for each region is vital for improving local productivity, generating jobs, and enhancing economic stability at both district and city scales.

The administration of population services in Rumbai Timur District continues to face challenges following the regional expansion that required residents to update their civil documents. The SIPENDUDUK website was introduced to simplify digital submissions; however, its implementation has not been fully effective. A portion of the community, particularly older adults and individuals with low digital literacy, still struggles to navigate service flows and upload required documents. This study aims to evaluate the service quality of the SIPENDUDUK website in improving the effectiveness of civil administration services. A descriptive qualitative method was employed through observations and interviews with officers and service users. The findings indicate that although the website has facilitated administrative processes, its accessibility has not yet reached all user groups due to varying technological capabilities. The system shows adequate efficiency and stability, although several technical issues remain. Service security is maintained through controlled access and a simplified interface. User support is provided through direct assistance from the local office, including manual guidance and mobile outreach services. These results highlight that the success of digital services depends not only on system quality but also on user readiness. This evaluation is expected to contribute to improving the effectiveness, inclusiveness, and overall quality of population administration services in Rumbai Timur District.

This research examines the mentoring of nationalistic activities by students from the Al-Azhar Menganti Gresik Institute and field supervisors at MI Darunnajah Lebani Suko, Wringinanom District, Gresik Regency, in commemoration of Heroes' Day. Thru a descriptive qualitative approach, this program involves four main activities: the red and white parade, patriotic love songs, little warrior strokes (coloring and writing hero stories), and a colossal drama of patriotic fervor. These activities are creatively designed and based on direct experience to instill nationalistic values in elementary school students. The research results show a significant improvement in students in terms of courage, discipline, creativity, cooperation, and respect for national symbols such as the flag and national anthem. Collaboration between students as facilitators, teachers as pedagogical directors, and the school environment creates a conducive learning ecosystem where participatory methods are more effective than conventional approaches. This experiential learning approach not only enhances cognitive understanding of the struggles of national and local heroes but also builds emotional empathy and social skills. Positive impacts include high student enthusiasm, reduced learning boredom, and character strengthening in accordance with the Pancasila Student Profile, such as mutual cooperation and integrity. Overall, this mentoring program serves as a relevant model for non-formal character education that can be replicated in other schools to strengthen nationalism from an early age amidst the challenges of post-pandemic globalization and individualism.

This study examines the differences between Micro, Small, and Medium Enterprises (MSMEs) and large corporations in utilizing e-commerce platforms for digital promotion, particularly through collaborations with influencers. The rapid development of digital technology has reshaped business competition and created unequal access to market opportunities, where corporations benefit from strong financial capacity, formal contractual structures, and comprehensive legal compliance, while MSMEs often struggle with limited resources, inconsistent product legality, and informal promotional arrangements. This research aims to analyze comparative practices in digital promotion between the two business scales and evaluate how regulatory frameworks support digital fairness for MSMEs within Indonesia’s e-commerce ecosystem. Using a qualitative method that combines literature review and in-depth interviews with three influencers, the study reveals significant distinctions in collaboration patterns, compensation systems, marketing flexibility, and legal assurance. The findings indicate that MSMEs exhibit higher adaptability and openness toward emerging creators, whereas corporations demonstrate stronger professionalism but lower responsiveness due to bureaucratic structures. The research further highlights persistent digital inequality shaped by differences in legal awareness, operational capacity, and marketing strategy. These findings imply the importance of enhancing MSME digital literacy, strengthening contractual governance, and improving regulatory responsiveness to ensure equitable participation in the digital market. Strengthening cooperative efforts between government, digital platforms, and influencer communities is essential for building a fairer and more inclusive e-commerce environment.