This article explores the marketing strategies implemented by various banking institutions in Semarang City through a literature review approach. The study aims to analyze marketing practices that focus on service quality, customer satisfaction, community-based engagement, and Sharia-compliant innovation. The findings indicate that banks such as PT. BPR BKK Kota Semarang, Bank Jateng, BPR Arto Moro, and Bank Syariah Mitra Harmoni employ various strategies to reach diverse market segments by enhancing service quality, strengthening community ties, and integrating local cultural and Islamic values into their financial products. These strategies have been proven to improve customer satisfaction and loyalty. This study provides both theoretical and practical contributions to the development of locally responsive bank marketing strategies aligned with social and cultural needs.

The metaverse has emerged as a new domain within the digital economy, offering decentralized and participatory ecosystems driven by digital assets such as NFTs, tokens, and cryptocurrencies. Platforms like Decentraland, Roblox, and The Sandbox represent varied models of economic governance and user engagement. However, effective economic management strategies in these virtual environments remain underdeveloped. This study explores how the three platforms manage digital economies, focusing on asset governance, community incentives, and risk dynamics. Using an exploratory qualitative approach, data were collected through semi-structured interviews and document analysis, and then thematically analyzed using NVivo software. Results show decentraland emphasizes DAO-based transparency, Roblox relies on centralized monetization, and The Sandbox balances both in a hybrid model. The study concludes that successful economic strategies in the metaverse require integrating governance structures, incentive mechanisms, and social user interaction. These findings offer insights for building more adaptive, inclusive, and sustainable digital economic frameworks in virtual ecosystems.

n recent years, Environmental, Social, and Governance (ESG) initiatives have sprouted into the front and center of both the global and national investment stage. In Indonesia, while the regulators and corporations have made their attempt in the promotion of ESG practices, how much such practices are construed to be influential in investment decisions remains ambiguous. Therefore, this study aims at providing an empirical study of the impact of ESG initiatives on investment decisions in the Indonesian capital market, evaluate which ESG dimension is most influential, and look at the mediating role of investor perception. This study adopts a quantitative explanatory approach, using Structural Equation Modeling based on Partial Least Squares (SEM-PLS), with an estimation of 135 firms' ESG data along with the perceptions of 200 investors. The findings indicate that ESG initiatives exert a significant influence on investment decisions, and governance is the most prominent factor. Moreover, it was found that investor perception has a considerable mediating role in the relationship between ESG and investment decisions. This study thus offers a new approach to the literature on ESG in Indonesia, as it integrates and contextualizes the results while emphasizing the key role of investor perception in sustainable investment decision-making.

In today’s complex organizational environment, Emotional Intelligence (EI) plays a critical role in shaping the quality of economic decision-making by managers. This study investigates how the dimensions of EI—namely self-awareness, emotional regulation, and empathy—influence strategic decision processes across various industries. Using a descriptive qualitative approach with thematic analysis, data were gathered from semi-structured interviews with 10 senior managers, supported by observations and organizational documents. The findings reveal that EI serves as an internal mechanism that stabilizes cognitive processes under organizational pressure, reduces decision bias, and enhances the social legitimacy of economic decisions. The integration of EI fosters a balance between rational analysis and affective insight, leading to more ethical and adaptive decisions. This study offers an integrative model connecting EI dimensions with key stages of economic decision-making and provides practical implications for managerial training and organizational policy. It advocates for interdisciplinary approaches to better understand emotionally-informed economic behavior.

The rapid proliferation of Internet of Things (IoT) devices has introduced significant challenges, particularly in managing electronic noise, which can degrade system performance and data accuracy. This study explores the integration of IoT with edge computing as a novel approach to mitigate electronic noise. By leveraging edge computing, data processing is performed locally, reducing transmission distances and enhancing real-time noise reduction. The research employs a combination of field experiments and computational simulations to evaluate the effectiveness of this integration. Key metrics such as noise reduction level, system latency, energy efficiency, and signal quality were measured before and after the implementation of noise mitigation technologies. Results indicate a significant reduction in electronic noise, with noise levels decreasing from 75 dB to 55 dB (a 26.67% reduction). System latency improved by 66.67%, dropping from 120 ms to 40 ms, while energy efficiency increased by 30%. Signal quality, measured by Signal-to-Noise Ratio (SNR), improved by 100%, from 10 dB to 20 dB. These findings demonstrate that the integration of IoT and edge computing effectively mitigates electronic noise, enhances system performance, and optimizes energy consumption. The study concludes with recommendations for further optimization of signal processing algorithms and testing in more complex industrial environments.

The rise of digital technology has influenced Indonesian millennials' financial behavior, especially in digital investment. However, wider access to financial products is not matched with adequate understanding, often leading to impulsive decisions. This highlights the gap between financial inclusion and financial literacy, making it crucial to study how literacy affects investment behavior in the digital era. This research examines how millennial financial literacy impacts investment behavior and how the digital environment moderates this effect. A quantitative method was used with data from 200 millennials engaged in digital investment, collected through an online questionnaire. Data were analyzed using multiple linear regression and moderated regression analysis (MRA). Results show that financial literacy significantly and positively influences investment behavior (p < 0.001). Moreover, the digital era strengthens this effect—active use of fintech and online communities amplifies the impact of financial literacy on rational investment choices. Financial literacy, investment behavior, and digital factors are interlinked. The study's findings are valuable for developing digital-based financial education and designing investment platforms that both guide and align with millennial traits.

This study explores the use of slang in the first episode of Season 1 of the television series Ginny & Georgia, focusing on identifying the types of slang employed by the characters and interpreting their meanings within conversational contexts. The research applies a descriptive qualitative approach, utilizing Allan and Burridge’s (2006) theory to categorize slang types and Leech’s (1981) theory of meaning to analyze their meanings. The analysis reveals five categories of slang: Fresh and Creative, Flippant, Imitative, Acronyms, and Clipping, with Flippant slang emerging as the most frequently used. Each slang term is examined for its contextual meaning, uncovering various types of meanings such as Conceptual, Connotative, Social, Affective, and Reflective Meanings. Based on the findings, Affective Meaning appears most prominently, reflecting the characters’ emotional tones and interpersonal dynamics. While some types of meanings like Collocative and Thematic Meaning were absent, the findings underscore how slang in the series operates beyond casual speech, serving as a linguistic tool to express identity, emotion, and cultural nuance.

This study aims to explore the protection mechanisms for victims of sexual violence in Islamic boarding schools, with a special focus on the tragic case that occurred at the Yayasan Manarul Huda Islamic Boarding School in Bandung. Between 2016 and 2021, 13 female students were victims of sexual violence by the boarding school owner, and nine of them gave birth to children. This case highlights the weakness of the protection system in Islamic boarding schools and the imbalance in power relations between kyai and students. This study uses a qualitative approach through a literature study method to analyze legal documents, journals, and relevant reports related to child protection and sexual violence in religious educational institutions. The results of the study indicate that the main factors that exacerbate the situation are the lack of a safe reporting mechanism, the lack of technical regulations governing child protection in Islamic boarding schools, and a patriarchal culture that silences the voices of victims. This study also found the importance of the involvement of families, communities, and state institutions in building a preventive, responsive, and curative child protection system. Recommendations include the formation of internal policies in Islamic boarding schools, the establishment of a child protection task force, and active cooperation with external institutions such as the Ministry of Religion and the Indonesian Child Protection Commission. A confidential reporting system and regular training are needed for all parties in the Islamic boarding school to create a safe and dignified learning environment.

Urinary incontinence (UI) significantly impacts the quality of life in older adults, often resulting from multifactorial causes, including age-related changes and systemic health issues. Emerging evidence highlights the role of lipid metabolism in influencing bladder and pelvic floor function through vascular integrity, inflammation control, and tissue repair. Lipid parameters, such as apolipoproteins, HDL, LDL, total cholesterol, triglycerides, and their ratios, provide insights into metabolic health and its association with UI. This study aims to identify specific lipid-related predictors, advancing the understanding of metabolic factors in UI and informing targeted prevention and management strategies for aging populations. This study used multiple linear regression analysis to assess the relationship between lipid panel predictors and urinary incontinence in 93 elderly respondents at Bina Bakti Nursing Home. The analysis identifies apolipoprotein B, Apo B/Apo A ratio, total cholesterol, and triglyceride-to-HDL ratio as significant predictors. These variables actively influence urinary incontinence through metabolic and vascular pathways, with both positive and negative associations. Apolipoprotein B, Apo B/Apo A ratio, total cholesterol, and triglyceride-to-HDL ratio predict urinary incontinence, highlighting lipid-related impacts on vascular health, inflammation, and tissue integrity for improved risk stratification.

The rapid development of information technology has made it easier to access various sources of information, but it has also increased the risk of plagiarism, especially among university students. To maintain academic integrity and the quality of education, plagiarism detection is essential. This study aims to develop a plagiarism detection system using the Knuth-Morris-Pratt (KMP) algorithm combined with the Jaccard Similarity method to measure the similarity between documents. The system is designed to analyze Indonesian-language essay documents in Word (.docx) and PDF (.pdf) formats that do not contain images or tables. The detection process begins with data preprocessing steps, including case folding, tokenizing, stopword removal, and stemming, to enhance efficiency and accuracy. The system is developed using the Python programming language and the Flask framework. Test results show that the system can detect plagiarism with an average accuracy of 98.66%. The level of similarity between documents is then categorized into three levels: Minor, Moderate, and Severe Plagiarism. This system is expected to serve as an effective tool in minimizing plagiarism practices in higher education and supporting the creation of an honest and responsible academic culture.