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In the face of global economic uncertainty and property market fluctuations, companies in the property and real estate sector are required to maintain profitability. This sector contributes significantly to the national GDP, but it has also faced pressure due to declining demand and instability in the growth of the real estate sector's GDP from 2021 to 2024. Profitability is a key indicator of a company's sustainability, influenced by various internal factors such as liquidity, firm size, and gender diversity in leadership. The target population of this inquiry encompasses property and real estate enterprises enumerated on the Indonesia Stock Exchange throughout the 2021–2024 interval. Through the application of purposive sampling, a total of 52 data observations were delineated as the empirical sample. The dataset was subjected to scrutiny employing multiple linear regression procedures facilitated by SPSS software version 26. The empirical outcomes substantiate that liquidity, firm size, and gender diversity simultaneously influence profitability. Partially, liquidity has a positive and significant effect on profitability, while gender diversity has a negative and significant effect. In contrast, firm size does not have a significant influence on the profitability of property and real estate companies listed on the Indonesia Stock Exchange during the 2021–2024 period.

This study investigates the impact of auditor competence and red flag awareness on fraud detection ability, examining the moderating role of professional skepticism. As fraudulent financial reporting poses a critical threat to the integrity of financial disclosures and stakeholder trust, understanding the key factors influencing an auditor's detection capabilities is essential. This study employed a quantitative approach, gathering data from auditors at Public Accounting Firms (KAP) in Bali Province via a four-point Likert scale questionnaire. The data were subsequently analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4 software. The findings indicate that both auditor competence and an awareness of red flags significantly and positively enhance fraud detection capabilities. Conversely, professional skepticism, when analyzed for its direct influence, demonstrated a significant negative effect on this ability. Furthermore, skepticism exhibited a complex moderating role: it significantly weakened the positive relationship between competence and fraud detection, while not significantly moderating the link between red flags and detection ability. These results provide crucial theoretical contributions by revealing the nuanced and sometimes counter-intuitive role of professional skepticism. Practically, they inform policy for audit firms and regulatory bodies, suggesting that while fostering competence and red flag awareness is vital, the application of skepticism requires a more sophisticated and refined approach to truly enhance audit quality and overall fraud detection effectiveness.

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.

The rapid development of digitalization and innovation has become a key driver in improving business processes and the competitiveness of organizations worldwide. This study is the first comprehensive bibliometric analysis examining the relationship between digitalization and innovation in business processes, to map the intellectual structure of this field, track the development of its themes, and identify remaining research gaps. This analysis, which utilizes data from Scopus processed using VOSviewer and Biblioshiny software, covers publications from 2010 to 2024 and employs co-occurrence, co-authorship, and thematic evolution techniques. The results show a rapid growth in publications since 2016, peaking at over 110 publications in 2024. Eight key thematic clusters stand out: Industry 4.0, artificial intelligence, robotic process automation, blockchain, drivers, and agile business process management. Despite the field's maturity, it still suffers from high fragmentation, strong geographic concentration, and a reliance on cross-sectoral research designs. As a result, longitudinal insights remain limited, and digital transformation failure rates remain high, reaching up to 70%. This research presents the first quantitative and visual roadmap of global knowledge flows in this domain and underscores the need for longitudinal, geographically inclusive, and people-centric research to move beyond single-point understandings to a sustainable, context-sensitive framework that enhances both the theoretical depth and practical success of digital-based business process innovation

The objective of this study is to directly analyze and illustrate the compositioneof the auditecommittee, which consists of financial knowledge, independence and the quantity of members on the committee, concerning the financial statement quality of energy sector industries listed on the IDX in 2023-2024.High-quality financial statements are a crucial component reflecting the outcome of the accounting process and are vital for stakeholders in decision-making. Despite regulatory requirements for audit committees, corporate financial statements in Indonesia often contain earnings management or accounting irregularities, indicating that the audit committee's very existence is insufficient to guarantee financial statements' quality. A numerical approach with a causal-comparative approach is utilized in this investigation. The secondary quantitative data are obtained from companies’ yearly financial statements, annual reports, and corporate governance disclosures published on the official IDX website. The data are examined using EViews software for panel data regression, going through many steps, including descriptive statistics, classical assumption testing, panel data model selection, and regression analysis for hypothesis testing. The audit committee's size, objectivity, and financial acumen make up the study's independent variables. Meanwhile, financial statement quality as the dependent variable is measured through earnings quality proxy using the discretionary accruals calculation approach (Jones model or Modified Jones model). Specifically, this research seeks to deliver theoretical and practical benefits for regulators in formulating corporate governance policies, give companies a comprehension of the importance of an effective audit committee, and help investors make informed investment choices.

The concept of green business performance has been an interesting topic for research among well-known scholars. Green business has become crucial for advancing sustainability and fostering innovation. Green business performance has become the global requirement due to the recent economic disaster, and green measures have been considered the leading solution for it. This study aims to explore how sustainability intersects with strategic business practices, offering actionable insights for aligning environmental sustainability with economic growth. To find worldwide research trends, bibliometric analysis was performed using R studio and VOSviewer software on 3007 scientific publications from Scopus from 2021 to 2024. Bibliometric analysis uses key words to enable the study of specific details, within the main topics of research, within a domain, and relationships at the micro-level. These methods facilitated an in-depth exploration of the evolution and impact of green business for sustainability. This study bridges existing gaps by providing actionable insights into how green business drive sustainable development, offering value to researchers, policymakers, and business leaders seeking to integrate environmental sustainability with economic growth.

This study aims to analyze the impact of government expenditure development and government budgeting on the social assistance recipients affected by floods. The research approach uses a quantitative method with a total of 50 respondents selected through sampling techniques. Data processing was conducted using SPSS software with various statistical tests, including validity test, reliability test, multiple linear regression, t-test, and F-test. The results show that the development of government expenditure has a significant impact on the condition of the social assistance recipients. Additionally, government budgeting also has a significant impact on the effectiveness of social assistance distribution after the disaster. Simultaneously, both variables have a strong influence on the social assistance recipients, as reflected by the significant F-test value and the coefficient of determination (R Square) of 0.518. This means that 51.8% of the variation in the condition of social assistance recipients can be explained by the development of government expenditure and government budgeting. These findings highlight the importance of appropriate expenditure and budgeting policies to enhance the effectiveness of social assistance distribution, especially in disaster situations.

This study was conducted to analyze the implementation of financial management and accounting practices at a Coffee Shop in South Jakarta operating within the MSME sector, with a focus on the importance of structured financial management and the application of standardized accounting as a fundamental element in supporting business sustainability. The research employed a qualitative descriptive method through interviews, direct observations, and document review. The findings indicate that the Coffee Shop has applied a cash-based recording system and utilizes a simple point of sales (POS) application to monitor cash flow and sales transactions. However, the recording of fixed assets, depreciation calculations, and the recognition of liabilities have not fully complied with the guidelines of FAS MSMEs, resulting in financial information that remains limited, lacks transparency, and does not provide a comprehensive overview of the business’s financial condition. Therefore, this study highlights the need to improve human resource capabilities in accounting and to implement simple yet credible accounting software to support more accurate, efficient, and accountable financial reporting. With more professional financial management, business owners will be better equipped to make strategic decisions, strengthen stakeholder trust, and enhance the competitiveness and long-term sustainability of the Coffee Shop.

This study aims to determine the relationship between learning motivation and learning outcomes in SMAW welding engineering among eleventh-grade students at SMKN 2 Solok. This research employed a quantitative method with a correlational approach. The population consisted of all students from classes XI TPM 1 and XI TPM 2, totaling 51 students, using a total sampling technique. Learning motivation data were collected through a validated and reliable questionnaire, while learning outcome data were obtained from post-test scores in the SMAW welding subject. Data were analyzed using the Pearson Product Moment correlation test with the assistance of SPSS software. The results showed a correlation coefficient of r = 0.783 with a significance value of 0.000 < 0.01, indicating a strong, positive, and statistically significant relationship between learning motivation and students’ learning outcomes. These findings suggest that higher learning motivation leads to better learning outcomes in SMAW welding engineering. Therefore, learning motivation plays an important role in improving students’ academic performance. This study is expected to provide useful insights for teachers and schools in developing instructional strategies that enhance students’ motivation and learning outcomes.

The hospitality sector faces major challenges, including fierce competition, low occupancy rates, and high operating costs, especially post-COVID-19 pandemic. This article examines how adaptation strategies, particularly through digital investments, affect customer satisfaction and hotel occupancy rates. This study uses a mixed method approach, combining quantitative and qualitative methods. Qualitative data was collected through in-depth interviews with managers, staff, and guests at five hotels in Semarang, Indonesia, to identify key factors for successful adaptation. Qualitative data are analyzed using MAXQDA software. Quantitative data were analyzed by multiple regression. The results show that investment priorities are a key driver of successful adaptation, although supporting factors such as improved facilities, quality of service, and the involvement of all personnel. Quantitative findings show that hotel adaptation strategies significantly affect customer satisfaction (influence of 47.10%) and occupancy rate (influence of 38.40%). Digitalization enhances operational efficiency, allowing staff to focus on personal interactions. Technologies like AI-based recommendations and mobile check-in directly improve the overall guest experience, correlating with loyalty. The conclusion of the study is that strategic digital investments, improved service quality and active staff engagement, are key to improving customer satisfaction, optimizing occupancy rates, ultimately, driving hotel revenue growth in the post-pandemic era.

The Society 5.0 era requires younger generations to develop strong digital literacy skills, not only in terms of technical technology use but also in understanding digital business administration and legal compliance. This community service program aims to enhance digital accounting literacy among students at MAN 3 Bekasi through training on accounting software and guidance on online registration of the Taxpayer Identification Number (NPWP). The activity was conducted using several methods, including material delivery, live demonstrations, independent practice, and evaluation using pre-test and post-test assessments. The results show a significant increase in participants’ knowledge, with an average improvement of 89.75% after attending the workshop. Furthermore, evaluation feedback indicates that participants expressed a very positive response toward the activity in terms of relevance, content delivery, and implementation process. Therefore, this program successfully contributed to improving students’ readiness to face digital transformation in the fields of accounting and tax administration

The Society 5.0 era requires younger generations to develop strong digital literacy skills, not only in terms of technical technology use but also in understanding digital business administration and legal compliance. This community service program aims to enhance digital accounting literacy among students at MAN 3 Bekasi through training on accounting software and guidance on online registration of the Taxpayer Identification Number (NPWP). The activity was conducted using several methods, including material delivery, live demonstrations, independent practice, and evaluation using pre-test and post-test assessments. The results show a significant increase in participants’ knowledge, with an average improvement of 89.75% after attending the workshop. Furthermore, evaluation feedback indicates that participants expressed a very positive response toward the activity in terms of relevance, content delivery, and implementation process. Therefore, this program successfully contributed to improving students’ readiness to face digital transformation in the fields of accounting and tax administration

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

This study aims to examine the effect of Environmental, Social, and Governance (ESG) disclosure, Return on Assets (ROA), and Enterprise Resource Planning (ERP) on tax avoidance in energy sector companies listed on the Indonesia Stock Exchange during the 2021–2024 period. This research employs a quantitative approach using secondary data obtained from annual reports and sustainability reports. The sample was selected using a purposive sampling technique, resulting in 112 observations. Multiple linear regression analysis was conducted using Stata 16 software. The empirical results indicate that ESG, ROA, and ERP simultaneously have no significant effect on tax avoidance. Partially, each independent variable also shows no significant influence. These findings suggest that ESG implementation and ERP adoption have not directly affected corporate tax behavior, while profitability is not a primary determinant of tax avoidance in the energy sector. This study contributes to the existing literature by incorporating ERP as a novel variable in tax avoidance research, providing additional insight into the role of integrated information systems in corporate taxation practices.

Texture creation has been one of the important aspects in creating 3D environment. It could support an object that could be identified by the viewer. There has been software that providing the creation of a texture for a playable 3D game asset. The purpose of this research was to find the method of making a wall texture and to show the in-app parameters that could be applied. The objective of this research is to find any possible limitation toward using the software. As a step to make exploration thoroughly, a brick wall design has been made with initial modelling in ZBrush and Maya app. Followed by the usage of Substance 3D Painter as a variable to control the texture modification. There was more in-depth explanation in creating a defined surface texturing with in-app technical parameters.

This study aims to determine the effect of Electronic Word of Mouth on Purchase Decisions (a case study of Glad2Glow skincare products). The population of this study consists of consumers who use Glad2Glow skincare products, with the sampling technique using accidental sampling. This research employs a quantitative method. The object of this study is users of Glad2Glow products who purchase skincare products at Glowtica Beauty Store. Data were collected through questionnaires measured using a Likert scale. The data analysis technique used is simple linear regression, processed with the assistance of SPSS software. The results of the t-test indicate that the Electronic Word of Mouth variable (X) has a significant effect on Purchase Decisions, with a significance value of 0.000 < 0.05 and a t-value of 6.069 > t-table of 2.03224. Therefore, it can be concluded that Electronic Word of Mouth has a significant effect on the Purchase Decision of Glad2Glow skincare products. Based on the results of this study, it can be concluded that Electronic Word of Mouth has a positive influence on the purchase decision of Glad2Glow skincare products.

Pengujian perangkat lunak merupakan tahap penting dalam memastikan kualitas dan keandalan sistem sebelum digunakan secara luas. Salah satu metode yang umum digunakan adalah black box testing, yaitu pengujian yang berfokus pada fungsionalitas perangkat lunak tanpa memperhatikan struktur internal kode. Dalam penelitian ini, metode black box testing diterapkan dengan menggunakan teknik state transition untuk menguji sistem appointment klinik berbasis web “Citra Medica”. Pengujian dilakukan dengan memetakan alur status pengguna melalui diagram transisi, kemudian membuat skenario uji untuk setiap perubahan keadaan. Hasil pengujian menunjukkan bahwa seluruh fungsi sistem berjalan sesuai dengan spesifikasi, dengan tingkat keberhasilan pengujian mencapai 100% pada setiap skenario transisi. Metode ini terbukti efektif untuk mendeteksi kesalahan logika dan memastikan kestabilan sistem selama perpindahan status pengguna.

This study aims to analyze the effect of financial literacy and financial inclusion on the financial management of Micro, Small, and Medium Enterprises (MSMEs) in Makale District. Sound financial management is an important factor for the sustainability and growth of MSMEs; therefore, an empirical examination of the factors influencing it is necessary. This study employs a quantitative approach using a survey method. Data analysis is conducted through multiple linear regression with the assistance of SPSS statistical software version 26. The research population includes all MSME actors in Makale District, with a sample of 88 respondents selected using a random sampling technique to ensure equal participation opportunities. The independent variables in this study are financial literacy and financial inclusion, while the dependent variable is MSME financial management. The results indicate that financial literacy has a positive and significant partial effect on MSME financial management. This finding suggests that the better MSME actors understand financial concepts and practices, the better their ability to manage business finances. In contrast, financial inclusion does not have a significant partial effect on financial management. However, financial literacy and financial inclusion simultaneously have a significant effect on financial management. The coefficient of determination of 69.3% indicates that most of the variation in MSME financial management can be explained by these two variables. This study concludes that improving financial literacy is a key factor in enhancing MSME financial management.

This study aims to analyze the effect of service quality, store atmosphere, and word of mouth on repurchase intention of Batik Lochatara Kediri consumers. This research employs a quantitative approach with a causal associative design. Data were collected through questionnaires distributed to 96 respondents who are customers of Batik Lochatara Kediri, selected using accidental sampling. The research instrument was measured using a five-point Likert scale. Data analysis was conducted using multiple linear regression with the assistance of SPSS software, preceded by validity, reliability, and classical assumption tests. The results reveal that partially, word of mouth has a positive and significant effect on repurchase intention, while service quality and store atmosphere do not show a significant effect. However, simultaneously, service quality, store atmosphere, and word of mouth have a significant influence on repurchase intention. These findings indicate that positive consumer recommendations and shared experiences play a more dominant role in encouraging repurchase intention in the context of local batik MSMEs. Therefore, strengthening word-of-mouth strategies is essential to enhance customer loyalty and business sustainability.

This study aims to investigate the empirical impact of population size and unemployment rates on economic growth in Central Kalimantan Province. The research focuses on the regional context of Central Kalimantan, utilizing a longitudinal dataset covering the eleven-year period from 2013 to 2024. To achieve the research objectives, the study employs quantitative analysis through the SPSS software package, utilizing multiple linear regression as the primary analytical tool to examine the relationship between the dependent variable (economic growth) and the independent variables (population and unemployment). The findings of the analysis reveal a divergent impact between the two independent variables. The results indicate that the population has a significant and positive influence on economic growth in Central Kalimantan during the 2013-2024 period, suggesting that demographic factors play a crucial role in regional expansion. Conversely, the unemployment rate was found to have no significant effect on economic growth within the same timeframe. Furthermore, the study conducted a comprehensive suite of classical assumption tests to ensure the validity and reliability of the statistical model. The results of these diagnostics confirm that the regression model adheres to the assumption of normality, shows no evidence of multicollinearity among the variables, and is free from symptoms of heteroscedasticity. Additionally, the analysis concludes that the model does not exhibit any issues related to autocorrelation. Consequently, the regression model is deemed statistically robust and appropriate for providing an accurate representation of the economic dynamics in Central Kalimantan.