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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.

This study aims to evaluate the effects of profitability, leverage, liquidity, and cash-flow shocks on the financial distress of companies in the hotel, restaurant, and tourism subsector listed on the Indonesia Stock Exchange during the period 2021 to 2024. The research approach employed is quantitative, using logistic regression analysis. The data analyzed are secondary data obtained from the annual financial statements of the respective companies. The results of the study indicate that, simultaneously, the four independent variables significantly influence financial distress. However, based on partial testing, each variable, namely Return on Assets (ROA), Debt to Equity Ratio (DER), Current Ratio (CR), and cash flow shock, does not show a significant relationship with financial distress. These findings imply that the risk of financial distress in this industry cannot be explained solely through a single financial indicator; instead, a more holistic approach is required. This study provides essential contributions to both management and investors in assessing companies' financial condition and formulating appropriate strategic decisions.

In the investment world, stock returns are the leading indicator of a company’s performance and the basis for investor decision-making in the capital market. Fluctuations in stock returns reflect market expectations of the company’s prospects. The retail sector in Indonesia is facing significant pressure from post-pandemic shifts in consumer behavior and increased competition. This study aims to analyze the effect of financial distress, company size, liquidity, operating cash flow, and accounting profit on stock returns in retail sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the period 2021 to 2023. This type of research is causally associated with a quantitative approach. The data used is secondary, in the form of financial statements from retail companies. The sampling technique used was purposive, yielding a total of 39 data points from 13 retail companies. Data testing was carried out using SPSS version 24. The results showed that partially, the variables of financial distress, company size, liquidity, and accounting profit had no significant effect on stock returns. Meanwhile, operating cash flow positively impacts stock returns. These findings indicate that fundamental indicators are not always the main determinants of stock returns. Therefore, investors are advised also to consider external factors such as market sentiment, macroeconomic conditions, and government policies that may have a greater influence on stock performance in the capital market.

This study aims to analyze the effect of profitability, leverage, and liquidity on firm value in food and beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2024 period. Profitability is measured by Return On Assets (ROA), leverage by Debt to Equity Ratio (DER), and liquidity by Current Ratio (CR), while firm value is proxied by Price to Book Value (PBV). The study employs a quantitative approach using multiple linear regression analysis. The sample consists of 25 companies selected through purposive sampling, with a total of 125 secondary data observations obtained from annual financial statements. The results indicate that, partially, profitability, financial risk, and liquidity have a positive and significant effect on firm value. Simultaneously, the three independent variables also significantly affect firm value, with an adjusted R² of 43.4%, meaning that 56.6% of the variation in firm value is explained by other factors outside the model. These findings support agency theory and signaling theory, which suggest that strong financial performance, optimal debt management, and adequate liquidity provide positive signals to investors, thereby enhancing firm value.

This study examines how company size, asset growth, tangibility, leverage, and total asset turnover affect profitability in consumer manufacturing companies listed on the Indonesia Stock Exchange from 2019 to 2023, using secondary data collected via purposive sampling. The independent variables in this study include the natural logarithm of total assets, asset growth (this year’s total assets relative to the previous year), and tangibility (the fixed asset ratio to total assets). Leverage uses the debt-to-asset ratio, and total asset turnover uses the total asset turnover ratio, while the dependent variable of profitability uses return on assets. Of the 108 companies in the population, 19 that met the research sample criteria were selected, yielding 95 observations. Data analysis was conducted using multiple linear regression, accompanied by classical assumption tests and hypothesis testing through F-tests and t-tests. The findings of this study reveal that asset growth has a significant positive effect on profitability, while leverage shows a significant negative effect. However, firm size, tangibility, and total asset turnover do not exhibit significant relationships with profitability. This study contributes both theoretically and practically to understanding the internal determinants of financial performance in the consumer sector and serves as a reference for management.

This study conceptually examines a self-supervised multi-scale fusion framework designed to enhance accuracy and computational efficiency in medical image segmentation, a domain where data scarcity and annotation cost remain major challenges. Traditional supervised approaches are constrained by their reliance on extensive labeled datasets, limiting applicability in real-world clinical environments. Self-supervised learning (SSL) mitigates this issue by extracting supervisory signals directly from unlabeled data, enabling the model to learn rich feature representations without human annotation. Simultaneously, multi-scale fusion architectures integrate global contextual information with fine-grained local features, supporting robust segmentation across varying anatomical structures and image resolutions. Through a qualitative methodology involving library research and content analysis, this study synthesizes state-of-the-art SSL-driven segmentation techniques and highlights how adaptive multi-scale fusion mechanisms address limitations of existing convolutional and transformer-based architectures. The analysis indicates that combining SSL and multi-scale strategies leads to more generalizable, scalable, and computationally efficient segmentation pipelines suitable for diverse medical imaging modalities. The proposed framework represents a promising direction for developing next-generation diagnostic tools capable of handling sparse labels, complex textures, and real-time deployment constraints.

This study examines the emerging paradigm of federated intelligence architectures as a secure, privacy-preserving, and scalable foundation for data-driven innovation across AI, IoT, and cloud ecosystems. With billions of interconnected devices generating massive heterogeneous data, traditional centralized machine-learning models face critical limitations, including privacy risks, regulatory constraints, latency, and single points of failure. Through a qualitative content-analysis approach, this paper synthesizes contemporary research on federated learning, blockchain integration, zero-trust governance, and edge intelligence to formulate a comprehensive understanding of distributed AI infrastructures. The findings highlight that federated learning enables collaborative model training without exposing raw data, significantly enhancing privacy, security, and compliance. Moreover, combining blockchain with federated learning strengthens auditability, model integrity, and trust, while zero-trust principles provide continuous verification and adaptive security enforcement across devices. Edge-AI integration further reduces latency and bandwidth consumption, enabling real-time analytics in resource-constrained IoT environments. Collectively, these elements contribute to the formation of cognitive ecosystems capable of autonomous, interoperable, and context-aware operations. The study underscores the transformative potential of federated intelligence while identifying critical gaps that inform future research trajectories.

In recent years, with the rapid development of artificial intelligence, many innovative changes have been made in the field of intelligent mobile robot development. In the field of control and navigation of mobile robots, learning-based methods have many advantages over traditional ones. The study of mobile robot control methods using deep reinforcement learning is a remarkable area in the development of mobile robots that must operate in dynamic environments. In the previous studies, the proposed robot control algorithms using deep reinforcement learning are mostly based on the given target point and obstacle information, the robot path planning is performed, and the corresponding control is based on the obtained path. The DDPG-based method is a typical example. However, in dynamic environments, DRL based robot path planning requires a state of target point and obstacles information, which leads to a large amount of computation, resulting in extremely long convergence time and even non-convergent cases. In this paper, we propose a new method for mobile robot control in dynamic environment that solves the dimensional problem by extracting the features of the configuration of obstacles using autoencoder and learning the DDPG algorithm based on the obtained features. Simulation results show that the proposed algorithm can effectively solve the mobile robot control problem in dynamic environment.

Dynamic programming (DP) is a foundational technique for solving multistage optimization problems; however, its classical formulation often incurs a cubic time complexity, rendering it impractical for large-scale real-world applications. This study proposes an accelerated dynamic programming framework that leverages quadrilateral inequality and convex monotonicity theory to significantly reduce computational overhead. By formally establishing the structural conditions under which DP decision boundaries exhibit monotone behavior, the proposed method eliminates redundant state transitions and maintains a sequence of admissible decisions through an efficient stack-based mechanism. The resulting algorithm achieves a worst-case complexity of O(n2) and can be further optimized to O(n) when convex monotonicity holds, representing a substantial improvement over traditional O (n3) techniques. Experimental validation using the classical stone-merging problem demonstrates that the accelerated method executes more than 60 times faster than the standard approach for large inputs, while maintaining identical optimal results. These findings confirm that embedding geometric regularities into DP formulations not only enhances performance but also broadens the applicability of dynamic programming to computation-intensive optimization tasks. This research contributes a mathematically grounded, scalability-oriented solution for accelerating dynamic programming, with implications for logistics, production planning, data segmentation, and other large-scale decision systems.

This article examines the evolving discourse on granting legal personhood to Artificial Intelligence (AI) by analyzing jurisprudential foundations, global regulatory frameworks, and emerging challenges in liability attribution. As AI systems acquire higher autonomy, opacity, and decision-making independence, traditional human-centered legal structures struggle to assign responsibility for AI-generated harms. Through a qualitative methodological approach, involving library research and content analysis, this study evaluates whether limited or functional legal personhood can serve as a viable solution to accountability gaps created by advanced AI systems. The discussion explores key themes including AI autonomy, black-box decision processes, digital identities in virtual environments, metaverse avatars, and the boundaries of existing tort and contract law. Comparative insights from the European Union, the United States, and India highlight significant divergences in regulatory approaches, particularly regarding “electronic personhood,” strict liability models, and AI-specific safeguards. Findings indicate that while full personhood is premature, a hybrid framework—combining functional personhood, risk-based regulation, and AI-focused accountability mechanisms—could enhance legal clarity, promote responsible innovation, and strengthen public trust. This study contributes to the ongoing global effort to conceptualize AI legal personhood within modern socio-digital ecosystems.

Penelitian ini bertujuan mengembangkan strategi ekonomi pesisir berkelanjutan di Teluk Berau, Distrik Kokas, Kabupaten Fakfak, melalui integrasi tradisi lokal kera-kera ke dalam kerangka Business Model Canvas (BMC). Tradisi kera-kera berfungsi sebagai mekanisme adat untuk melestarikan sumber daya alam serta meningkatkan kesejahteraan masyarakat melalui pengelolaan hasil laut secara kolektif. Penelitian ini menggunakan pendekatan kualitatif deskriptif partisipatoris, dengan teknik pengumpulan data berupa wawancara mendalam, observasi partisipatif, dokumentasi, dan diskusi kelompok terarah. Analisis data dilakukan dengan model interaktif Miles, Huberman, dan Saldaña. Hasil penelitian menunjukkan bahwa praktik buka tutup kera-kera berdampak pada peningkatan kuantitas dan kualitas hasil tangkapan, mendorong aktivitas ekonomi lokal, serta membentuk dasar model BMC yang merefleksikan kearifan lokal dan prinsip keberlanjutan. Analisis SWOT digunakan untuk merumuskan strategi adaptif dalam menghadapi peluang dan ancaman internal maupun eksternal. Penelitian ini menawarkan kebaruan ilmiah melalui integrasi tradisi adat ke dalam model bisnis modern sebagai upaya revitalisasi ekonomi pesisir sekaligus pelestarian lingkungan. Temuan ini menjadi rujukan dalam pengembangan strategi ekonomi berbasis kearifan lokal dan pedoman kebijakan daerah.

This study aims to determine the role of the Tourism Office in promoting Letvuan Paradise Tourism Village and what obstacles are faced by the Tourism Office of Southeast Maluku Regency in carrying out promotions in Letvuan Paradise Tourism Village, Southeast Maluku Regency. This research method uses a qualitative descriptive method. Data collection techniques used observation, interviews, and literature studies. The results of the study indicate that the Southeast Maluku Regency Tourism Office plays a significant role in promoting the Letvuan Paradise Tourism Village through facilitation, mentoring, and collaboration with various parties. Promotion is carried out through official social media, annual events, and efforts to include Letvuan Paradise in the National Event Calendar (CEN). Promotion in the tourism sector is a means of communication to introduce a tourist destination and build a positive image, thereby increasing the number of visitors and providing economic benefits to the surrounding community. In addition to Hawang Cave, promotion also highlights local potential such as arabusta coffee, Japanese bunkers, and community culture. The Tourism Office also supports Pokdarwis and MSMEs through training and involvement in various activities. This encourages community and village government participation in tourism promotion. Obstacles faced include limited infrastructure, budget, and the use of digital technology. Overall, the Tourism Office plays a significant role in building the image of Letvuan Paradise, but sustainable development still requires infrastructure improvements, consistent promotion, and community independence.

Nirun Beach is located in Ohoi Elaar, Southeast Maluku Regency, and has become one of the prominent tourist destinations. This research aims to identify the factors affecting tourists’ interest in visiting Nirun Beach in Ohoi Elaar Ngursoin, Southeast Maluku Regency, and to determine the most dominant factor. The research method used is a quantitative method with a questionnaire instrument using a Likert scale, involving 100 tourist respondents. The research results show that the factors affecting tourists’ interest include economic factors (70%), environmental factors (84.75%), technology and social media (77.31%), accessibility and infrastructure (71.12%), and the interest in visiting (79%). Among these five factors, the environmental factor scored the highest, indicating that the beauty and sustainability of Nirun Beach’s nature are the main attraction for tourists. The conclusion of this study is that, although other factors such as the economy, accessibility, and infrastructure have an impact, the environmental aspect remains the dominant factor. The recommendations from this study are the need for improvements in facilities, accessibility, tourism promotion through social media, and involving the local community in tourism management to increase the appeal of Nirun Beach.

This study aims to analyze the influence of financial knowledge, financial attitudes, and self-control on personal financial management among students of the Management Study Program at the Faculty of Economics, Universitas Kristen Indonesia Toraja, class of 2022. The research uses a quantitative approach, distributing questionnaires to 83 respondents selected through the Slovin formula. The data is analyzed using multiple linear regression, as well as validity, reliability, classical assumption, and hypothesis testing. The results show that financial knowledge has a positive and significant effect on personal financial management, while financial attitudes and self-control do not have a significant partial effect. However, simultaneously, the three independent variables have a significant impact on the students' personal financial management. These findings suggest that students' personal financial management is influenced by a combination of financial understanding, attitudes toward money management, and the ability to control their financial behavior. This indicates the importance of enhancing financial knowledge as a key factor in improving personal financial management among students, while attitudes and self-control need further attention to achieve better financial management.

This study aims to analyze the influence of the Live Streaming and Flash Sale features on TikTok Shop on purchasing decisions for Maybelline cosmetic products. The research employs a quantitative approach using a survey method, with a questionnaire distributed to 79 female students of the 2022 Management Program at the Faculty of Economics, Universitas Kristen Indonesia Toraja. Based on the analysis results, it was found that the Live Streaming feature has a positive and significant impact on purchasing decisions, while Flash Sale does not show a significant effect. Simultaneously, both variables have a significant effect on purchasing decisions, with an R² value of 15.1%. This indicates that other factors outside of the variables studied influence purchasing decisions by 84.9%. The findings suggest that the Live Streaming feature is more effective in influencing purchasing decisions compared to Flash Sale, highlighting the importance of utilizing interactive and real-time features to enhance consumer purchase intent on e-commerce platforms like TikTok Shop. This study provides insights for marketers in designing more targeted digital marketing strategies on social media platforms.

The purpose of this study is to determine the effect of lecturer certification on the performance of lecturers at the Universitas Kristen Indonesia Toraja. This study uses a quantitative method with a multiple linear regression approach, and data processing was carried out using SPSS version 23. The data collection procedures included observation, interviews, questionnaires, and documentation. The study involved 56 respondents who were selected using simple random sampling with the Slovin formula. The results of the t-test showed that lecturer certification has a significant effect on lecturer performance. This was evidenced by the significance value of 0.000 (p < 0.05) and a t-value of 7.099, which is greater than the t-table value of 2.005. This means that lecturer certification (variable X) positively affects lecturer performance (variable Y). The conclusion of this study is that lecturer certification has a positive and significant impact on improving lecturer performance at Universitas Kristen Indonesia Toraja. This study recommends that the university pay attention to the importance of lecturer certification to support the improvement of teaching quality and lecturer performance in the future.

This study examines the SWOT analysis in facing the business competition of motorcycle sales at PT. Tunas Honda Rantepao. The purpose of this research is to understand the internal and external conditions of the company and how strategies can be applied to address the existing challenges. The research method used is qualitative, with data collection through interviews and documentation. Data analysis techniques are carried out through data collection, data reduction, and data presentation steps. The results of the study indicate that the rapid advancement of technology poses a challenge for PT. Tunas Honda Rantepao, forcing this motorcycle dealer to continually innovate in its marketing strategy. Based on the analysis of the company's internal and external conditions, a SWOT analysis was conducted to evaluate the strengths, weaknesses, opportunities, and threats faced. From this analysis, various strategic alternatives were identified that can be applied to improve performance and competitiveness of PT. Tunas Honda Rantepao in the motorcycle market, both in terms of utilizing technology, improving service quality, and developing more effective marketing.

This study aims to determine and analyze the effect of product completeness (X1) and service quality (X2) on purchasing decisions at PT. Sulo Rantepao, North Toraja. This research uses a quantitative approach with a multiple linear regression method. The data were collected through the distribution of questionnaires to 97 respondents. The results of the study indicate that partially, the product completeness variable (X1) does not have a significant effect on purchasing decisions, as shown by a significance value of 0.099 > 0.05 with a t-value of 1.667 > t-table value of 1.661. Meanwhile, the service quality variable (X2) is proven to have a positive and significant effect on purchasing decisions, with a significance value of 0.00 < 0.05 and a t-value of 8.540 > t-table value of 1.661. Simultaneously, product completeness (X1) and service quality (X2) have a significant effect on purchasing decisions (Y), as evidenced by a significance value of 0.00 < 0.05 and an F-value of 77.331 > F-table value of 3.09. The R-squared value of 0.614 indicates that the two independent variables are able to explain 6.14% of the variation in purchasing decisions, while the remaining 38.6% is influenced by other variables outside this study.

This study examines the comparative fatwas of Muhammadiyah and Nahdlatul Ulama (NU) regarding the Islamic legal ruling on smoking in the Indonesian context. The research employs a qualitative method through a literature-based analysis of official documents, academic journals, and decisions from Bahtsul Masā’il and the Majelis Tarjih dan Tajdid. The findings indicate that Muhammadiyah declares smoking as prohibited (ḥarām) because it contradicts the objectives of Islamic law (maqāṣid al-syarī‘ah), particularly in preserving life (ḥifẓ al-nafs) and wealth (ḥifẓ al-māl). Conversely, NU categorizes smoking as reprehensible (makrūh) on the basis that no definitive textual evidence explicitly forbids it, while also considering socio-economic factors within society. Muhammadiyah adopts a normative-preventive approach, whereas NU emphasizes a cultural-educational one. The difference between the two fatwas reflects not a contradiction but a constructive ikhtilāf, enriching the diversity of Islamic jurisprudence in Indonesia.

The development of digitalization has brought significant progress in the dissemination and accessibility of creative works, particularly through digital platforms that enable rapid and widespread distribution. The digitalization of creative works provides significant opportunities for creators and the creative industry to expand market reach and increase creative productivity. However, on the other hand, this progress also poses various challenges, particularly related to the increase in copyright infringement such as piracy, unauthorized duplication, and illegal distribution of digital content. This article aims to examine criminal acts against copyright infringement in the digital era based on Law Number 28 of 2014 concerning Copyright. The research methods used are literature study and case analysis to identify types of digital copyright infringement, the application of criminal law, obstacles in law enforcement, and possible solutions. In addition, this article also analyzes the effectiveness of applicable legal regulations and the impact of copyright infringement on the sustainability of the creative industry. The results of the study indicate that firm and adaptive law enforcement to technological developments is crucial to protect creators' rights and maintain the sustainability of creativity in the digital era.