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The rapid development of the sea transportation industry produces a massive and complex volume of transaction data, requiring strategic management to support managerial decision-making. This research aims to implement the Executive Information System on SeaPass in order to evaluate the performance of ship ticket sales. The research method uses data visualization with a two-level drill-down mechanism, which allows the presentation of information hierarchically from general summaries to specific details. The methodological stages include needs analysis, user interface (UI) design using Figma, front-end implementation with HTML, CSS, and JavaScript, database integration, and system testing through Black Box Testing. The results showed that the SIE implementation successfully integrated operational data, including schedules, ships, and manifests, into an interactive dashboard. The two-level drill-down feature provides the ability for executives to identify operational anomalies and market fluctuations in real-time. In conclusion, the system significantly enhances executive data analysis capabilities, transforming complex transaction data into accurate strategic information, thereby supporting more precise business decision-making and adaptive to the dynamics of the marine transportation market.

Flood is a frequent natural disaster in Indonesia, often exacerbated by delays in information delivery from conventional manual monitoring systems. This study aims to design and build an automatic flood early warning system based on the Internet of Things (IoT) integrated with a web dashboard and WhatsApp notifications. The system utilizes the ESP32 microcontroller and MaxBotix MB7389 ultrasonic sensor for real-time water level data acquisition. The Research and Development (R&D) method was employed, focusing on device accuracy validation and system integration. The measured data is transmitted to a .NET-based server and stored in a PostgreSQL database. Results indicate that the system functions according to design. Sensor accuracy testing demonstrated a high degree of precision (99.12% - 100%) compared to manual measurements. Furthermore, the system successfully sends timely warning notifications via WhatsApp when water levels exceed predefined thresholds, providing a more effective solution than manual monitoring to enhance community preparedness.

Economic forecasting is becoming increasingly important year after year, especially during crises such as the pandemic of COVID-19 and the Russia-Ukraine war. Its development can be seen from the use of basic statistical models to the increasingly widespread use of machine learning technology. Economic forecasting plays an important role in helping to formulate policies and is also a reliable tool for researchers in dealing with uncertainty. Global crises, such as inflationary pressures due to the pandemic and supply chain disruptions from the Russia-Ukraine conflict, have prompted increased research in this field in an effort to anticipate economic shocks and emphasize the urgency of forecasting to prepare strategies for dealing with future uncertainty. This literature review uses the Scopus database with 2561 publications from 2020 to 2025, analyzed using R Studio with a bibliometrix approach (specifically biblioshiny) and VOSviewer to map relevant thematic connections. This analysis shows that economic forecasting is greatly influenced by market uncertainty and geopolitical factors, and at the same time influences public policy formulation and financial stability. Research contributions from Indonesia are still limited, with only 40 documents, thus emphasizing the need to strengthen economic forecasting studies in Indonesia to support monetary policy and national financial stability.

Digital entrepreneurship has become a transformative phenomenon in the modern economy, changing the way businesses are developed and run through digital technology. Although the literature on digital entrepreneurship is growing rapidly, comprehensive mapping of the evolution of knowledge and research patterns is still limited. This study analysis the development of digital entrepreneurship in academic literature through bibliometric analysis of the Scopus database to identify research trends, knowledge structures, and future directions. The analysis was conducted on 1,815 publications from 681 sources (1988-2025) written by 8,023 researchers, using R Studio (bibliometrix) and VOSviewer. The results show exponential growth with an annual growth rate of 17.22%, as well as five main theme clusters: digital business models, digital innovation, social entrepreneurship, e-commerce, and fintech. Thematic evolution shifted from traditional entrepreneurship (1988–2010) to digital transformation (2011-2018) to new technology integration (2019-2025). The level of international collaboration reached 26.39%, with the United States, China, and the United Kingdom as the main contributors. These findings provide a research roadmap for identifying research gaps, collaboration opportunities, and trending topics in digital entrepreneurship.

Currently, patients experiencing early symptoms of skin disease caused by the exanthema virus are unable to immediately consult a dermatologist due to the high cost and limited time available for specialists in hospitals. Therefore, the author needs to develop an expert system application that can address this issue. Through this application, users can consult with the system, much like an expert, to diagnose their symptoms and find solutions to their problems. This expert system is designed to provide answers based on whether the symptoms are correct or not, or to provide several recommended answer choices based on the symptoms. To diagnose skin disease caused by the exanthema virus, the author used the Case-Based Reasoning method. The CBR method is a weighting technique that compares new cases with previous cases. The diagnosis is based on data provided by the patient and expert, which is then analyzed using case-based reasoning and stored as a knowledge database in the expert system. Therefore, this expert system can help identify solutions for problems experienced by patients suffering from skin disease caused by the Exanthema Virus.

Climate risk finance has emerged as an increasingly important field of research along with the growing urgency to address climate change and its impacts on the global financial system. Climate change poses real risks to the stability of the international economy and financial systems. Climate risk finance represents an approach that encompasses various financial instruments in supporting climate change mitigation and adaptation. Although the term climate risk finance has not been widely used explicitly as a single keyword, the concept that integrates climate risk and financing is reflected in related keywords such as climate risk, climate finance, and climate change. This study employs a bibliometric analysis method using the Scopus database, supported by analytical tools such as VOSviewer and R Studio, to explore the development of research on climate risk finance. The study identifies publication patterns, international collaborations, and emerging themes within the related literature. The findings show that the publication rate on climate risk finance is relatively moderate each year, but has experienced growth in the last decade. The evolving understanding in this field is expected to strengthen the resilience of financial systems and support sustainable strategies to address long-term climate risks.

This study analyzes the synergy between human resource development (HRD), work culture, and decision-making systems in enhancing productivity and organizational performance. The approach used is a descriptive qualitative literature review, with sources from peer-reviewed articles from 2021-2025 obtained through databases such as Google Scholar and ScienceDirect. The research findings indicate that HRD can improve employee competence by up to 28.7%, while work culture contributes 41.4-55% to motivation and collaboration within teams. Decision-making systems, such as AHP (Analytical Hierarchy Process) and BI (Business Intelligence), play a role in optimizing operational efficiency by up to 65%. The synergy of these three elements forms a more adaptive organization to change. One example of the implementation of this synergy can be seen in PT X Jakarta, which experienced a 28% increase in output and employee satisfaction reached 85%. However, the main challenge faced is resistance to change, which can be overcome through effective communication. The practical implications of this study include recommendations for holistic organizational transformation, especially in Indonesia, to face the challenges of global disruption.

The integration of big data in the financial sector has increasingly attracted scholarly attention, particularly in areas such as risk management, fraud detection, algorithmic trading, and investment optimization. Given the rapid development of this field, it is essential to map research trends and identify emerging directions that shape the future of financial innovation. This study applies a bibliometric approach using 3,829 articles retrieved from the Scopus database from 1981 to 2025, with data processed through R Studio and the Bibliometrix-Biblioshiny application. The objective is to explore the intellectual landscape of big data finance and reveal research frontiers as well as thematic evolution. The results show a sharp increase in publications after 2015, alongside the growth of fintech and artificial intelligence applications, with dominant themes including blockchain integration, risk analytics, and predictive modelling. Cross-disciplinary and cross-regional collaborations continue to expand. These findings provide a comprehensive overview of how big data has shaped financial studies and offer insights for potential future research directions.

Artificial Intelligence (AI) has become a significant driver of innovation in the banking sector, especially in the context of post-pandemic digital transformation. AI is widely utilized in areas such as fraud detection, credit evaluation, risk management, and customer interaction, attracting considerable interest from both academics and industry professionals. This research explores the recent advancements in AI within the banking industry, focusing on studies published between 2020 and 2025. A bibliometric approach is employed, using data from the Scopus database and bibliometric tools like VOSviewer and R Studio to visualize keyword networks and track emerging trends. The study aims to identify influential authors, journals, and countries contributing to AI research in banking. By analyzing these developments, the research highlights the contributions of AI to improving operational efficiency, data security, and financial inclusion, particularly in the Indonesian context. This work offers valuable insights into the ongoing integration of AI in the banking sector and its potential to shape future financial services, emphasizing its relevance to both global and regional markets.

Smart industry has become an important trend in the development of Industry 4.0, especially in promoting the creation of efficient systems in the manufacturing sector. Various countries and studies are encouraging the application of technologies such as IoT, digital twins, artificial intelligence, and smart factories to improve industrial efficiency and sustainability. Therefore, studies related to smart industry are important and necessary especially on the context of smart manufacturing in order to see the direction of future research trends. This study uses a qualitative approach with literature data from the Scopus database covering the period 2020 to 2025. Research trend analysis was conducted through data processing using Bibliometric analysis in R Studio and the VOSviewer applications. To identify the latest research trends regarding smart industry, particularly in the context of Industry 4.0 and smart manufacturing, this analysis can provide a comprehensive picture of future research developments and directions within a global context.

The digital era has transformed the financial sector through the integration of FinTech, making it more susceptible to increasingly complex cyber threats. As these risks rise, there has been a significant increase in academic research to better understand the cybersecurity challenges within the financial sector. This study aims to explore the development of cybersecurity research globally within this field. By utilizing bibliometrics, the research analyzes literature data collected from the Scopus database over the last five years. The analysis was conducted using VOSviewer and RStudio to identify dominant clusters, with cybersecurity and network security as the central themes linking various sub-fields, including artificial intelligence, cyberattacks, and phishing. The findings reveal areas of extensive research and highlight gaps that require further exploration. This study provides valuable insights for researchers and professionals in the cybersecurity field, offering a roadmap for future investigations and the identification of underexplored areas that need attention. Ultimately, this research contributes to advancing knowledge in the financial sector’s cybersecurity landscape and assists in shaping future research directions.

Financial inclusion has become a key driver in promoting sustainable development, especially in the era of Industry 4.0, which is characterized by rapid digitalization, technological innovation, and the transformation of financial services. Although academic interest in this topic continues to grow, research in this field has not been systematically mapped, resulting in limited understanding of global trends and thematic evolution. This study uses bibliometric analysis (BA) to explore developments, intellectual structures, and key research focuses in financial inclusion research. Data were collected from the Scopus database for the period 2015–2025, using keywords related to financial inclusion, thus ensuring a comprehensive dataset for analysis. Bibliometric methods were applied using analytical tools such as VOSviewer and R Studio to support the assessment. The results of the analysis show a consistent increase in the number of publications over the last decade, reflecting growing academic attention. The main contributions came from India, China, and the United States, with increasing participation from universities in Africa and Southeast Asia through international collaboration. The main research focus has shifted from microfinance and poverty alleviation to more digital-oriented themes, including fintech, digital finance, blockchain, and green finance. This study contributes by mapping the structure and trends of financial inclusion research and providing insights for policymakers and academics in developing inclusive financial systems that support national strategies such as the SNKI, MSME digitalization, and financial literacy programs in Indonesia to achieve sustainable development goals.

The digital economy and e-commerce are rapidly transforming global markets, driving efficiency, inclusivity, and innovation. However, these developments also produce unintended consequences, particularly regarding environmental sustainability. This study aims to examine the relationship between digital transformation, the expansion of e-commerce, and their impact on carbon emissions and socio-economic outcomes. Using bibliometric analysis and VOS Viewer to map and analyze research trends from leading academic databases, this paper identifies key themes, knowledge clusters, and research gaps in the intersection of digital economy, logistics, and sustainability. The findings indicate that technological advances foster economic growth and greater accessibility but simultaneously contribute to rising energy consumption, logistics intensity, and carbon footprints. These results highlight the dual nature of digitalization as both a catalyst for inclusive development and a driver of environmental pressures. The study argues that an integrated policy framework is crucial to leverage the benefits of digital transformation while mitigating its environmental costs. It emphasizes the importance of green innovation, sustainable infrastructure investment, and inclusive e-commerce practices as key strategies for ensuring long-term socio-economic resilience. Ultimately, the paper contributes to the policy discourse by positioning innovation, inclusivity, and environmental stewardship as complementary rather than competing forces, thereby offering a pathway for future digital economy development that is both equitable and sustainable.

Advances in accounting technology and economic decision-making have resulted in many important risk assessment tools that support the decision making process. In the past, risk assessment depended on personal opinions and manual analysis, which often resulted in inaccurate estimates and delays in decision-making. However, with these risk assessment tools, we can now identify, analyze, and mitigate various risks that can affect financial and economic outcomes in a more accurate and efficient manner. This study aims to discuss technology in the form of risk assessment tools as an aid in decision-making and identify trending topics related to the use of risk assessment tools from 2020-2025, particularly in Indonesia. This study uses a qualitative approach and collects data from the scopus database of 1.827 articles selected from 2020 to 2025. In understanding research from the scopus database, bibliometric analysis was used in this study and using analysis tools such as R Studio and Vos Viewer. The results of the study show a significant increase in publications related to risk assessment tools with a growing trend toward international collaboration. The dominant themes that emerged include decision making, artificial intelligence, climate change, health risks, and financial markets. In addition, the increasing number of publications with international collaboration trends shows that the use of risk assessment tools has become a global standard that Indonesia needs to adapt. The government can use these findings as a basis for formulating policies that are more adaptive to technological developments.

Global climate change has prompted analysis of emission control policies, including carbon trading mechanisms and carbon taxes, to achieve a low-carbon economy. This study utilizes a bibliometric approach (2020–2025) with the Scopus database, which is processed using the RStudio application with Bibliometrix and Biblioshiny analysis and also uses the VOSviewer application, to identify publication trends and the effectiveness of emissions policies in different economic contexts, such as G20 countries or developed countries with developing countries. Thematic analysis results show dominant topics such as emissions trading, carbon capture, renewable energy, and a focus on economic development and technological innovation. The reviewed literature confirms that higher carbon tax rates are more effective in reducing emissions in G20 countries, while in developing countries, the implementation of a combination of strict carbon taxes and emissions trading mechanisms can promote substantial decarbonization. Overall, this bibliometric study confirms the growing research interest in green economy solutions and supports the urgency of adaptive, evidence-based emissions policies in various economic contexts.

The rise of financial technology (fintech) has significantly reshaped global investment over the last decade. Fintech innovations are increasingly applied in areas such as digital investment platforms, robo-advisors, blockchain-based assets, and cryptocurrency trading. The adoption of fintech in investment continues to grow due to the rising demand for accessibility, transparency, and efficiency in financial markets. Fintech has the potential to democratize investment by lowering entry barriers, expanding financial inclusion, and offering diverse investment instruments for retail investors. Therefore, research on fintech and investment has become an essential topic in recent years. This study uses a qualitative approach with data obtained from the Scopus database, which includes a total of 4,794 articles on fintech and investment published in the last decade (2020–2025). In addition, several software tools such as R Studio, VOSViewer, and Publish or Perish were used for data processing and bibliometric visualization. This study aims to analyze the development of research trends in fintech-driven investment, explore how technology is changing investor behavior, and provide insights for policymakers and practitioners in strengthening a sustainable and inclusive investment ecosystem.

Green innovation has become a crucial approach to addressing sustainability challenges within global economic and environmental contexts. This study maps the development of green innovation research through a bibliometric analysis using data from the Scopus database covering the period 2021–2024. Bibliometric techniques were applied with VOSviewer and R Studio to examine publication trends, citation patterns, author collaboration, and keyword networks. The results show a significant growth of publications in the last five years, with major themes focusing on sustainable development, environmental technology, and economic implications of green innovation, while leading contributions come from China. Influential journals in innovation and environmental management are identified as key publication outlets, and keyword analysis reveals the integration of green innovation into sustainability strategies and economic policy discussions. This study contributes to a clearer understanding of the intellectual structure and emerging directions of green innovation research, offering insights for scholars, business practitioners, and policymakers in advancing sustainable innovation practices.

Abortion remains a complex reproductive health issue due to the interplay of multiple interrelated determinants. This study aimed to map the factors influencing the incidence of abortion based on recent scientific evidence. A literature review design was applied by analyzing ten selected articles published within the last five years and retrieved from major scientific databases. The selection process was conducted systematically through title, abstract, and full-text screening based on predefined inclusion criteria. The extracted data included study characteristics, type of abortion, examined determinants, and key conclusions. The synthesized findings indicate that abortion incidence is shaped by a combination of biological, social, and healthcare system related factors. Clinical determinants such as maternal age, endocrine disorders, uterine anatomical abnormalities, obstetric history, anemia, and hypertension play a substantial role in spontaneous and recurrent miscarriage. In contrast, structural factors including income level, contraceptive access, and legal regulations predominantly influence induced abortion. The discussion highlights that abortion should not be viewed as an isolated clinical event, but rather as the cumulative outcome of risks operating across multiple levels of influence. In conclusion, abortion represents a multifactorial phenomenon that requires comprehensive prevention strategies extending beyond medical interventions alone. These strategies should also address healthcare accessibility and broader social conditions. This review contributes to a deeper understanding of the complexity of abortion determinants and provides an evidence-based reference for developing more effective preventive approaches in the future.

Industri café di Indonesia menghadapi tantangan dalam mengelola menu yang tidak laris, yang dapat menimbulkan kerugian akibat penumpukan bahan baku dan inefisiensi operasional. Penelitian ini bertujuan untuk memprediksi menu tidak laris menggunakan algoritma Decision Tree sebagai dasar penyusunan strategi bundling dan promosi yang efektif di café. Metode penelitian menggunakan pendekatan Knowledge Discovery in Database (KDD) yang mencakup tahapan seleksi data, pra-pemrosesan, transformasi, data mining, dan evaluasi pola. Dataset penelitian terdiri dari 500 record transaksi café yang dibagi menjadi 80% data latih (400 record) dan 20% data uji (100 record). Variabel yang digunakan meliputi jenis promo, nama menu, harga, kategori harga, cuaca, dan label kelarisan. Hasil penelitian menunjukkan bahwa model Decision Tree mampu memprediksi menu tidak laris dengan akurasi 84%, precision 87,50% untuk kelas Laris, dan 77,78% untuk kelas Tidak Laris. Analisis pohon keputusan mengidentifikasi bahwa jenis promo merupakan faktor paling dominan dalam menentukan kelarisan menu, diikuti oleh nama menu, harga, dan kondisi cuaca. Promo buy 1 get 1 terbukti paling efektif meningkatkan penjualan secara konsisten, sementara menu tanpa promo cenderung tidak laris. Menu seperti Coconut Steezy dan Steezy Coffee menunjukkan performa stabil bahkan dengan diskon ringan. Temuan ini memberikan rekomendasi strategis bagi pengelola café dalam mengoptimalkan promosi, mengurangi pemborosan bahan baku, dan meningkatkan profitabilitas melalui pendekatan berbasis data yang dapat diimplementasikan secara praktis.

Stunting is a chronic nutritional problem characterized by a child’s height being inappropriate for their age, particularly among children under five years old. One of the interventions implemented to prevent stunting is immunization. However, immunization coverage, especially complete basic immunization, has not yet reached the target, including in Medan City. Therefore, this literature study aims to explore the determinants of complete basic immunization coverage in Medan City using the Google Scholar database. The literature search identified nine articles that were extracted and discussed in this study. The determinants of complete basic immunization coverage include individual maternal factors such as age, education level, knowledge, attitudes, and mothers’ beliefs or perceptions toward immunization; social support factors including family support, economic conditions, and prevailing norms and cultural practices within families and communities; as well as health service factors. Comprehensive and integrated interventions are urgently needed to achieve optimal complete basic immunization coverage in Medan City.