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This study examines the influence of financial literacy, Fear of Missing Out (FOMO), and influencer marketing on Generation Z's decision to use Buy Now Pay Later (BNPL) services in Dompu Regency. The rapid development of financial technology has encouraged the widespread adoption of BNPL as an alternative digital payment method, particularly among young consumers. However, the increasing use of this service also raises concerns regarding financial decision-making and consumer behavior. This research employed a quantitative approach using a survey method involving 100 Generation Z respondents selected through purposive sampling. Data were collected using a structured questionnaire with a five-point Likert scale and analyzed using multiple linear regression. The findings indicate that financial literacy has a positive and significant effect on BNPL usage decisions. Likewise, FOMO significantly influences individuals' decisions to utilize BNPL services, while influencer marketing also demonstrates a positive and significant contribution to users' decisions. Simultaneously, the three independent variables significantly affect BNPL usage decisions, explaining 27% of the variance in the dependent variable. These findings suggest that financial knowledge, psychological factors, and social influence collectively shape Generation Z's financial behavior. Therefore, strengthening financial literacy and promoting responsible use of digital financial services are essential to encourage more informed and sustainable financial decision-making.

This research aims to implement Business Intelligence and the TOPSIS method in a Decision Support System for selecting the best-selling products in retail stores through an analytical Dashboard. Retail businesses generate large amounts of transaction data every day, but the data is often only used for operational reporting and has not been optimally utilized for strategic decision making. This study integrates Business Intelligence technology, data Warehouse, ETL process, Dashboard Analytics, and TOPSIS method to analyze product sales patterns and determine the best-selling products based on several criteria such as sales quantity, stock turnover, profit level, customer demand, and sales frequency. The research method uses a system development approach consisting of data collection, dimensional modeling, ETL implementation, TOPSIS calculation, Dashboard design, and system evaluation. The results show that the implemented system can accelerate reporting processes, improve decision-making accuracy, and assist management in identifying strategic products quickly and interactively. The integration of TOPSIS with Business Intelligence Dashboards contributes to effective data-driven decision making in retail management.

Pelanggaran jam operasional kendaraan bertonase besar di kawasan Simpang Patal Kota Palembang masih sering terjadi dan menyebabkan kemacetan, risiko kecelakaan, serta kerusakan jalan. Penelitian ini bertujuan menganalisis alternatif kebijakan yang paling tepat untuk penertiban mobil barang di kawasan tersebut. Penelitian menggunakan metode deskriptif kualitatif melalui observasi, wawancara, dokumentasi, dan studi literatur. Analisis data dilakukan menggunakan model Miles dan Huberman, sedangkan evaluasi kebijakan menggunakan pendekatan Multi-Criteria Decision Analysis (MCDA) berdasarkan kriteria William N. Dunn. Terdapat tiga alternatif kebijakan yang dianalisis, yaitu mempertahankan kebijakan yang berlaku (status quo), revisi Perwali Nomor 26 Tahun 2019 dan implementasi Electronic Traffic Law Enforcement (ETLE), serta penyediaan kantong parkir (holding area) di kawasan Pelabuhan Sungai Lais. Hasil penelitian menunjukkan bahwa alternatif penyediaan kantong parkir (holding area) memperoleh skor tertinggi sebesar 91 dengan rata-rata 4,55 sehingga dinilai paling optimal dalam mengurangi pelanggaran, kemacetan, dan risiko kecelakaan serta mendukung transportasi perkotaan yang lebih tertib dan berkelanjutan.

Abstract:

Advancements in information technology encourage MSMEs to utilize information systems to enhance the effectiveness of their business management. Es Teh Arjuna, an MSME in Tegal City, faces challenges in monitoring partner sales and managing revenue because transactions are recorded manually using disparate methods; this results in slow data recapitulation, a risk of recording errors, and difficulty for the business owner in quickly accessing sales information. This study aims to analyze requirements, design, develop, and test a web-based information system for partner sales and revenue that provides information in  real-time. The Waterfall model was used for system development, while data collection involved observation, interviews, and a literature review. The system was developed using PHP and MySQL and tested via Black Box Testing. The results demonstrate that the system successfully integrates sales data from all outlets into a centralized database, streamlining the management of products, outlets, employees, cashiers, and sales transactions, as well as facilitating the generation of revenue reports for specific periods. Furthermore, the system enables the business owner to monitor sales performance more quickly, accurately, and systematically, thereby supporting decision-making and improving the operational efficiency of Es Teh Arjuna.

Digital technology advancements have greatly changed how small businesses manage their finances. This change is not only about recording transactions, but it also affects financial control, report preparation, and business decision making. Accounting Information System (SIA) came about as a solution to help small and medium businesses easily, organize, and accurately record their finances, as well as provide reliable financial information. This study aims to explain the role of the Accounting Information System in making it easier to manage the finances of small and medium businesses in the digital age, the benefits gained from using it, and the challenges faced during its implementation. The method used in this research is a literature review, which involves examining books, journals, and other related scientific publications, followed by analysis using a descriptive qualitative approach. Research findings show that using a digital-based Accounting Information System can improve business efficiency, speed up financial reporting, increase transparency, and make it easier for small and medium-sized businesses to get funding access. However, the implementation of the Accounting Information System still faces challenges such as a lack of technological understanding, limited infrastructure, and high implementation costs. Therefore, collaboration and support from various parties are needed to ensure the accounting information system is implemented effectively and sustainably in small and medium businesses.

The increasing emphasis on sustainable business practices has encouraged companies to integrate environmental and social responsibilities into their strategic and financial decision-making processes. This study investigates the influence of Green Accounting on Firm Value and examines the moderating role of Corporate Social Responsibility (CSR) within the Triple Bottom Line framework. A quantitative research design was employed using panel data from 23 energy, mining, and infrastructure companies listed on the Indonesia Stock Exchange during the 2022–2024 period, resulting in 69 firm-year observations. Secondary data were collected from annual reports and sustainability reports and analyzed using descriptive statistics, classical assumption tests, and Moderated Regression Analysis (MRA). The findings indicate that Green Accounting does not have a significant direct effect on Firm Value, while CSR also shows no significant direct influence. Furthermore, CSR is unable to significantly moderate the relationship between Green Accounting and Firm Value. These results suggest that sustainability initiatives implemented by Indonesian companies have not yet generated measurable short-term financial benefits, although they may contribute to long-term corporate legitimacy, stakeholder trust, and sustainable competitiveness. The study provides practical implications for corporate managers, investors, and policymakers by emphasizing the importance of strengthening sustainability reporting quality and integrating environmental and social strategies into long-term corporate value creation.

This study aims to analyze the effect of liquidity and profitability ratios on stock returns through Price to Book Value (PBV) in coal mining companies listed on the Indonesia Stock Exchange (IDX) during 2020-2024. The research uses secondary data analysis from financial reports of the companies collected through documentation techniques, and the data is analyzed using Partial Least Squares (PLS) based on Structural Equation Modeling (SEM). The results show that profitability significantly influences stock returns and PBV, while liquidity has a negative but insignificant effect on PBV and stock returns. Moreover, PBV does not mediate the relationship between liquidity and stock returns or profitability and stock returns. This study recommends that companies focus on improving profitability to enhance stock returns, while investors should consider profitability performance when making investment decisions. Recommendations for future research include adding other independent variables such as leverage or macroeconomic factors and expanding the sector and period coverage for greater generalization.

This study aims to analyze the effect of exchange rate on transfer pricing with tax minimization as a moderating variable. The research employs a quantitative approach using secondary data obtained from companies’ financial statements. The analytical methods include regression analysis and interaction testing to examine the moderating role. The results indicate that tax minimization does not strengthen the effect of exchange rate on transfer pricing, but instead weakens the relationship, leading to the rejection of the second hypothesis (H2). These findings suggest that companies tend to rely more on tax efficiency strategies rather than responding to exchange rate fluctuations in determining transfer pricing policies. This study implies that internal company factors play a more dominant role than external factors in influencing transfer pricing decisions.

This study proposes a computer vision-based system for automatically verifying the use of Personal Protective Equipment (PPE) in industrial environments. The system integrates the YOLOv8 object detection model, OpenCV for image processing, and a State Machine mechanism to manage the verification workflow. The verification process begins with employee identification through ID card scanning, followed by real-time detection of the head, safety helmet, and face mask using a camera, before generating a final PASS or FAIL decision. System evaluation was conducted using 250 testing scenarios to assess both model and system performance. The results show that the YOLOv8 model achieved an mAP@50 of 93.9%, while the overall verification system obtained 98.4% accuracy, 98.4% precision, 100% recall, and a 99.2% F1-score. The implementation of the State Machine contributed to a more stable and consistent verification process by ensuring that each inspection stage was executed in the correct sequence. These findings demonstrate that the proposed system can effectively support automated PPE compliance monitoring and has the potential to enhance occupational safety management in industrial workplaces. 

The surge in young investors in the country indicates that university students are increasingly drawn to the financial markets. Unfortunately, the soundness of students' investment choices often lacks a foundation of clear reasoning, as they remain swayed by social influences, limited insight, and the rapid technological advancements that facilitate access to investment opportunities. This study aims to unravel the determinants of students' investment decisions through the lens of the Theory of Planned Behavior (TPB), focusing on financial literacy, risk tolerance, and technology—three factors frequently examined in existing literature. A qualitative approach was adopted, involving a literature review of scholarly articles published between 2020 and 2024. Data gathered from relevant academic sources were analyzed using content analysis techniques to identify research patterns, conceptual relationships, and the consistency of prior findings. The results reveal that the Theory of Planned Behavior effectively explains students' investment decisions through the interplay of attitudes, subjective norms, and perceived behavioral control. Financial literacy emerges as the most robust and consistent determinant influencing investment decisions; risk tolerance shapes investment preferences; and technology acts as a catalyst, enhancing accessibility and convenience. These findings suggest that deepening financial literacy—supported by optimal technology use and adequate risk awareness—can empower students to make investment decisions that are rational, well-calculated, and long-term oriented.

This community-based project aimed to analyze the cash management system of the micro, small, and medium enterprise (MSME) Bakpia Juwara Satoe and develop recommendations to improve the company's financial performance. Cash management is a crucial but often overlooked aspect of MSME financial management, which can lead to cash flow problems, inaccurate record keeping, and poor management decisions. The methodology used included qualitative data collection through direct observation, in-depth interviews, and financial statement analysis. The project findings revealed that Bakpia Juwara Satoe lacked a functioning cash management system. There was no separation between cash receipts and disbursements, no standardized system for handling cash, and transaction recording remained manual and inconsistent. As part of the project, standard operating procedures (SOP) for cash management were developed, financial accounting training was conducted, and support was provided in creating simple cash flow statements. Following the implementation of these measures, record accuracy increased by 78%, and cash losses were reduced. It was determined that the implementation of efficient cash management contributed significantly to the improvement of Bakpia Juwara Satoe's financial performance.

Exports as a component of international trade contribute significantly to the development and growth of a country’s economy. In Indonesia, export activities are considered one of the key drivers in increasing national economic performance. This research seeks to evaluate the role of Indonesia’s exports to the United States within the Harmonized System (HS) Code 71 commodity classification, encompassing pearls, gemstones, precious metals, and jewelry products, in influencing Indonesia’s economic growth as reflected by Gross Domestic Product (GDP) at constant prices.The analysis focuses on three specific commodity groups: Pearls and Precious Stones (HS 71.01–71.05), Precious Metals and Metals Clad with Precious Metals (HS 71.06–71.12), and Jewelry and Related Articles (HS 71.13–71.18). A descriptive quantitative research design was employed, utilizing secondary time-series data collected for the 2015–2024 period. Data sources included the Indonesian Central Bureau of Statistics (BPS) and Trade Map. To assess the relationship between variables, this study adopted multiple linear regression analysis accompanied by classical assumption testing and hypothesis testing using both t-test and F-test procedures. The empirical findings demonstrate that export performance within the HS Code 71 category underwent considerable fluctuations throughout the observation period, reaching its peak in 2024.Furthermore, the statistical results indicate that each commodity sub-category contributes differently and exerts varying effects on Indonesia’s real GDP, both individually and collectively. The outcomes of this research are expected to provide useful references for government institutions in developing trade cooperation strategies and policy decisions, while also supporting business actors in strengthening the international competitiveness of Indonesian products.

The purpose of this study is to analyze the influence of Corporate Social Responsibility (CSR), Financial Distress, and Altman Z-Score on Dividend Decisions in automotive sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2025 period. This study is motivated by fluctuations in the Dividend Payout Ratio (DPR) in the automotive sector, which indicates changes in company dividend policy due to economic conditions, financial performance, and non-financial factors that influence management decision-making. The research method used is a quantitative approach with a causal associative research type to examine the relationship between the independent and dependent variables. The study population consists of automotive sector companies listed on the IDX, while the sample was determined using a purposive sampling technique based on certain criteria. Research data were obtained from annual reports and company financial statements for the 2020–2025 period. Data analysis was carried out using the Dividend Payout Ratio (DPR) as a proxy for dividend decisions and statistical testing to determine the effect of CSR, Financial Distress, and Altman Z-Score on company dividend, the data were processed using SPSS.

This study aims to analyze the effect of artificial intelligence (AI)-based demand forecasting and big data analytics on inventory optimization through prediction accuracy among e-commerce actors or marketplace sellers in Curug. This research employed an explanatory quantitative approach involving 100 respondents selected through purposive sampling based on predefined criteria relevant to the research objectives. Data were collected using a structured Likert-scale questionnaire and analyzed using Structural Equation Modeling Partial Least Squares (SEM-PLS) by evaluating the measurement model, structural model, and mediation effects. The findings reveal that AI-based demand forecasting and big data analytics have a positive and significant effect on prediction accuracy. Furthermore, prediction accuracy has a positive and significant effect on inventory optimization and significantly mediates the relationship between AI-based demand forecasting, big data analytics, and inventory optimization. These findings indicate that the integration of AI and big data analytics contributes to more accurate demand prediction, leading to improved inventory management performance. The implication of this study suggests that e-commerce actors should improve data quality, analytical capability, and the adoption of predictive technologies to support more accurate, efficient, and responsive inventory decisions, thereby enhancing operational performance and competitiveness in responding to dynamic market demand.      

This study aims to analyze normatively and juridically whether students in private schools are entitled to free basic education based on the Constitutional Court Decision Number 3/PUU-XXII/2024. Prior to this decision, the phrase “without charging fees” in Article 34 paragraph (2) of Law Number 20 of 2003 on the National Education System was often interpreted narrowly, applying only to public schools. This interpretation created discrimination in access to education for students in private schools, particularly those from low-income families. This research employs a normative juridical method with a statute approach and case approach. Primary legal materials include the 1945 Constitution of the Republic of Indonesia, Law Number 20 of 2003 on the National Education System, and Constitutional Court Decision Number 3/PUU-XXII/2024. Secondary legal materials consist of relevant scholarly literature, books, and journals. The analysis reveals that the Constitutional Court declared Article 34 paragraph (2) of the National Education System Law conditionally unconstitutional. The phrase must be interpreted to mean that the Central and Regional Governments are obliged to guarantee the implementation of compulsory basic education without charging fees, both for educational units organized by the government (public schools) and by the community (private schools). Consequently, students in private schools have the right to obtain free basic education as a constitutional right. Private schools are still permitted to charge fees from financially capable parents, but they are obligated to provide financial relief or full fee waivers for students from economically disadvantaged families. This decision has significant juridical implications for national education financing policy, particularly the need to revise derivative regulations and allocate School Operational Assistance (BOS) and Regional BOS funds to eligible private schools. This study complements previous research, which was largely empirical and regional in scope, by providing a comprehensive national normative juridical analysis.

This study examines the relationship between Indigenous Knowledge Systems (IKS) and legal autonomy within the Indian legal and constitutional framework. It explores how ancient Indian governance recognized legal pluralism through customary laws, village autonomy, tribal jurisdictions, and decentralized judicial systems. The study further analyzes the ecological and philosophical foundations of Indigenous Knowledge Systems, emphasizing the indigenous worldview that promotes harmony between humans and nature through principles of sustainability and environmental stewardship. Additionally, the research evaluates the legal challenges faced by indigenous communities under modern intellectual property regimes, particularly concerning communal ownership, oral traditions, and biopiracy. Constitutional protections such as the Fifth Schedule, Sixth Schedule, and the Forest Rights Act (2006), alongside landmark judicial decisions, demonstrate India’s efforts to safeguard indigenous rights and traditional knowledge. The study also highlights international legal mechanisms, including the Convention on Biological Diversity (CBD), the Nagoya Protocol, and WIPO initiatives, while emphasizing the need for stronger legal frameworks and international cooperation to ensure indigenous sovereignty and long-term protection of Indigenous

Child support rights after divorce constitute a fundamental right that must be protected to ensure children's welfare and development. However, many children do not receive adequate financial support because parents, particularly fathers, fail to fulfill their obligations after divorce. This study aims to analyze the legal regulation of child support rights after divorce and examine the legal protection available when these rights are neglected. The research employs normative legal research using statutory and conceptual approaches. Legal materials were collected through library research, including legislation, legal literature, scholarly journals, and relevant court decisions. The findings show that Indonesian law provides a comprehensive legal framework through the Marriage Law, the Child Protection Law, and the Compilation of Islamic Law, all of which affirm that divorce does not terminate parental responsibilities. Under Islamic law, the obligation to provide child support remains with the father. Legal protection is available through civil and criminal mechanisms, including enforcement claims and criminal liability for child abandonment. However, weak law enforcement, limited supervision of court decisions, and low legal awareness continue to hinder effective protection. Strengthening enforcement, increasing legal awareness, and enhancing state involvement are essential to ensure the fulfillment of child support rights after divorce.

Although MSMEs are crucial to the economy, the sustainability of non-franchise micro-enterprises is often hampered by suboptimal financial governance. Low utilization of financial information, lack of separation between personal and business finances, and unstructured cash flow management are challenges that can affect long-term business sustainability. This quantitative study aims to evaluate the impact of financial record keeping, capital planning, and cash cycle management on the sustainability of non-franchise micro-enterprises in Mekargalih Village, Garut Regency. Using a survey method and saturated sampling technique, data from 70 business owners were analyzed using multiple linear regression. The results of the study indicate that financial record keeping does not have a significant impact on business sustainability, indicating that recording activities are still administrative in nature and have not been optimally utilized as a basis for business decision-making. Conversely, capital planning and cash cycle management have been shown to have a positive and significant impact on business sustainability. Business owners who are able to plan capital needs and maintain smooth cash flow tend to be more able to maintain the stability of their business operations. Simultaneously, these three variables contribute 45.2% to business sustainability. This finding confirms that the ability to allocate capital andKeywords: business continuity; financial records; capital planning; cash cycle; micro-enterprises.

This study examines the growing debate surrounding the possibility of granting legal personhood to artificial intelligence (AI) systems within contemporary legal frameworks. As AI technologies become increasingly autonomous in decision-making, innovation, and economic interactions, questions arise concerning accountability, liability, and ethical governance. Using a qualitative library research approach, this study analyzes scholarly literature, legal theories, and global regulatory developments related to AI personhood. The discussion explores historical precedents of non-human legal entities, including corporations and natural objects, and compares them with emerging proposals for electronic legal personality. The findings reveal that while functional legal recognition may offer practical solutions for liability and compensation, current AI systems lack consciousness, moral agency, and intentionality required for full legal personhood. Consequently, most jurisdictions prefer human-centered regulatory models emphasizing transparency, oversight, and institutional accountability. The study concludes that extending legal personhood to AI remains premature and that adaptive governance frameworks are more appropriate for managing future AI-related legal challenges