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This study aims to evaluate the financial performance of PT Akasha Wira International Tbk during the period 2022 to 2024 using profitability ratio analysis. The ratios analyzed include Return on Assets (ROA), Return on Equity (ROE), Gross Profit Margin (GPM), Operating Profit Margin (OPM), and Net Profit Margin (NPM). The data used is sourced from official financial statements published through the Indonesia Stock Exchange website. Based on the results of the analysis, the company's financial performance is generally relatively good and shows stability over the past three years. This is reflected in the consistency of the profitability ratio which is at a favorable level, indicating the effectiveness of the company in managing assets, its own capital, production costs, and operational activities. Further analysis shows that the Return on Assets and Return on Equity show a stable trend with a slight increase, which indicates efficiency in asset utilization and capital management. Gross Profit Margin and Operating Profit Margin also show positive trends, indicating efficiency in managing production costs and operational activities. Net Profit Margin, although slightly volatile, remains within a range that reflects good profitability. In addition, the results of this evaluation also indicate that the company has the ability to adapt to market changes and dynamic economic conditions. The ability to maintain profit margins in the midst of economic fluctuations shows the resilience of the business model and operational strategy applied. These findings provide an idea that PT Akasha Wira International Tbk has been able to maintain a healthy performance despite being in a competitive business environment. Thus, the results of this evaluation can be used as a basis for strategic considerations by management in preparing long-term financial plans and decision-making, as well as a reference for investors in assessing the company's prospects.

This study aims to analyze the potential utilization of empty space on the second floor of the domestic terminal of Zainuddin Abdul Madjid International Airport (ZAM) Lombok to increase revenue from the non-aeronautical sector. The background of this study is based on the importance of optimizing airport assets to support long-term financial sustainability. This is crucial considering that the aeronautical sector is highly dependent on fluctuating flight traffic. Therefore, the development of the non-aerospace sector is a strategic alternative that needs to be seriously addressed. The research method used is descriptive qualitative, with data collection techniques through direct observation on site, interviews with airport management, and documentation studies. The results of the observation indicate that there is an empty space on the second floor of the terminal, specifically between the waiting room and a row of commercial tenants, which has not been optimally utilized. This area is considered to have a strategic position and quite high passenger traffic, so it has the potential to be developed into a new commercial facility. One of the proposed developments is a photobox service business unit with a local Lombok cultural theme. This concept is considered interesting because it combines digital technology with elements of cultural tourism promotion, in line with the trend of tourist needs for documentation and unique experiences. A feasibility analysis was conducted using the Business Model Canvas approach and the 7P marketing strategy (product, price, place, promotion, people, process, and physical evidence). The results showed that this idea is feasible from both an operational and marketing perspective. The study concluded that developing a photo booth business in an empty airport area has the potential to become a new, stable, efficient, and market-relevant source of revenue. Recommendations are given to airport management to immediately realize the utilization of this area to support the airport's role as a regional economic and tourism hub.

Blockchain logistics represents the integration of blockchain technology into the logistics sector, aiming to enhance efficiency, transparency, and security across supply chain processes. From an Islamic economics perspective, digital transformation must align with core values such as justice, transparency, and honesty to support the development of fair and sustainable logistics systems. The decentralized nature of blockchain offers promising solutions for building supply chains rooted in Islamic ethical principles. This study conducts a bibliometric analysis to examine the development and research trends of blockchain logistics within the context of Islamic economics. Using VOSviewer software, relevant scientific publications were analyzed based on bibliographic data sourced from reputable academic databases. Bibliometric parameters—such as the maximum number of authors per document and the minimum number of documents per author—were applied to identify key contributors and dominant research themes. The bibliometric mapping reveals the growth trajectory of blockchain logistics research framed by Islamic values. The visualization highlights research clusters, prominent authors, co-authorship networks, and publication trends that illustrate the evolution and scholarly interest in this interdisciplinary area. Emerging themes suggest a convergence between blockchain-driven logistics innovation and ethical economic practices advocated in Islamic teachings. The findings provide a comprehensive overview of the current landscape and collaboration opportunities in blockchain logistics research through an Islamic lens. This study contributes to the strategic positioning of future research by identifying gaps, potential synergies, and critical areas for development. Ultimately, it offers a foundational reference for scholars seeking to explore the integration of Islamic ethical principles within the advancement of blockchain-enabled logistics systems.

The era of digital transformation and the Indonesia Golden 2045 agenda demands a new paradigm in governance that prioritises inter-institutional collaboration to achieve effective and responsive governance. This transformation has been accelerated by the implementation of the Electronic-Based Government SIstem (SPBE) and the enactment of Law No. 1 of 2024 concerning Information and Electronic Transactions (ITE). This study analyses the implementation of good governance through digital transformation and inter-institutional collaboration, evaluates the challenges and opportunities in the digital era, and formulates optimisation strategies to support the achievement of Indonesia's Golden 2045. The research employs a normative juridical method, incorporating both conceptual and statutory approaches, and is reinforced by a systematic literature review analysis of current regulations and case studies of SPBE implementation in various regions across Indonesia. Data were collected through documentary studies of 35 laws and regulations and analysis of 40 academic literature sources from the period 2020-2025. The implementation of good governance through digital transformation shows positive results with SPBE success at the regional level, a 28% increase in government effectiveness, and the development of integrated service platforms serving 72 million transactions annually. However, challenges remain in regulatory harmonisation (47% overlapping authorities), digital capacity gaps (34% of institutions not yet optimal), and sectoral culture among institutions. Inter-institutional collaboration through digital transformation demonstrates positive trends in realizing good governance, but requires strengthening of digital legal frameworks, development of technological infrastructure, and organizational culture transformation to support the achievement of the Indonesia Golden 2045 vision.

The growing coffee production rate in Indonesia reflects an increasing public interest in coffee consumption. Fore Coffee, a local coffee shop, has taken advantage of this trend since 2018. However, strong competition from other coffee shops has placed Fore Coffee in third place in the Top Brand Award rankings for the past two years, indicating the need for more effective marketing strategies to boost purchase intention among potential consumers. This study aims to analyze the role of brand awareness in mediating the effect of social media marketing on purchase intention among prospective consumers of Fore Coffee in Denpasar City. The research was conducted with a sample of 120 respondents, using surveys with offline and online questionnaires. The sample was selected through a non-probability purposive sampling method. The data analysis was performed using path analysis and the Sobel test with SPSS version 25. The study’s results indicate that all hypotheses are supported. Social media marketing positively and significantly affects purchase intention, suggesting that effective social media strategies can directly influence consumers' willingness to purchase. Additionally, social media marketing positively impacts brand awareness, meaning that well-executed social media campaigns help consumers become more familiar with the brand. Furthermore, brand awareness has a significant positive effect on purchase intention, implying that increased awareness of Fore Coffee enhances the likelihood of purchase. The study also found that brand awareness partially mediates the relationship between social media marketing and purchase intention, indicating that social media marketing's impact on purchase intention is stronger when combined with high brand awareness. These findings emphasize the importance of integrating social media marketing with brand awareness strategies to improve consumer purchase intention.

As technology rapidly advances and social media adoption becomes widespread, Instagram and TikTok have evolved into essential marketing platforms, particularly for Micro, Small, and Medium Enterprises (MSMEs). This report aims to develop and implement a digital marketing strategy for the Seblak Opat Lima MSME using these two platforms. The business faced challenges in optimizing its digital marketing to reach a broader market, primarily due to a limited understanding of digital marketing among employees and a lack of consistency in social media account management. Our methodology involved field observation, which included creating a content timeline and content scripts to ensure consistency and relevance of published material. The analysis results show a significant increase on both social media platforms after the strategy was implemented, with a growth in followers and enhanced audience engagement, especially on TikTok and Instagram. Furthermore, analytics indicate that trend-aligned content combined with appropriate hashtag usage successfully expanded reach, increased profile visits, and encouraged more active audience interaction. Thus, the implemented digital marketing strategy proved effective in expanding the market and boosting sales for Seblak Opat Lima MSME.

This corpus-based study explores the acquisition patterns of English modal verbs by Indonesian EFL (English as a Foreign Language) learners through a comprehensive analysis of learner language data. The study utilizes a specialized learner corpus consisting of 2.5 million words drawn from both written and spoken productions of 450 Indonesian learners, covering various proficiency levels. The research focuses on examining the frequency patterns, semantic distributions, and error types associated with modal verb usage across the learner corpus. The study employs a combination of quantitative corpus linguistic methods and qualitative error analysis to uncover developmental trends and persistent difficulties in acquiring English modals. The findings highlight a significant underuse of epistemic modality, which expresses degrees of certainty, and an overreliance on core modals like "can," "will," and "must." Additionally, learners systematically avoid more complex modal constructions that are semantically nuanced and less frequent in their linguistic output. The analysis also reveals notable cross-linguistic influences from Indonesian, particularly in the areas of politeness marking and the expression of certainty. These interference patterns suggest that Indonesian learners may transfer modal expressions from their native language, leading to specific errors in the usage of English modals. Based on the findings, the study proposes a usage-based pedagogical framework that integrates corpus-informed instruction with explicit semantic mapping of modal meanings. This framework encourages teachers to address modal verb acquisition by emphasizing frequency-based approaches, contrastive semantic analysis, and corpus-driven awareness-raising activities. The research suggests that by focusing on the form-meaning-function relationships of modals in authentic contexts, learners can better understand and produce English modals accurately and appropriately. The findings have significant implications for enhancing modal verb instruction in EFL classrooms, especially for Indonesian learners.

Research on national banking using the Altman’s Z-Score analysis technique has been relatively extensive, but studies focusing specifically on banks indexed to SRI-KEHATI remain limited. The SRI-KEHATI Index is known as a benchmark for companies with strong sustainability, social responsibility, and good governance practices. This study aims to analyze the health trends of banks listed in the SRI-KEHATI Index during the 2015–2024 period by applying the second modified Altman’s Z-Score model (1993), which is widely recognized as a reliable indicator for assessing a company’s financial stability and risk of bankruptcy. The findings indicate that the overall Altman’s Z-Score trend of major banks within the SRI-KEHATI Index shows stability and a consistently healthy financial condition throughout 2015–2023. However, in 2024 there is a notable decline that requires further examination to determine whether it is caused by market fluctuations, structural challenges, or accounting adjustments. Despite this decrease, the overall financial health of the banks remains categorized as very good according to Altman’s model. The average Z-Score for all four banks analyzed is 6.457, which is well above the threshold of 2.6, indicating no significant bankruptcy risk. When evaluated individually, BMRI stands out as the healthiest with a Z-Score of 13.879, followed by BBNI with 5.971, BBRI with 3.175, and BBCA with 2.801. These results confirm that all four banks remain in a safe financial zone during the 2015–2024 period. Furthermore, the study’s four hypotheses are proven, reinforcing the argument that SRI-KEHATI indexed banks maintain strong financial resilience even amid post-Covid-19 challenges.

Indonesian people's shopping trends tend to shift from traditional markets to modern retail for reasons of convenience, location affordability, and speed of service. This study aims to determine whether Store Atmosphere and Experiential Marketing have a significant effect on consumer purchasing decisions at Alfamart Sadia I branch either partially or simultaneously. The data collection method uses a questionnaire with a Likert scale. The population in the study were all consumers of Alfamart Sadia I branch with a sample size of 96 people. Data analysis techniques used multiple linear regression, t-test and f-test. The results of the study showed that Experiential Marketing had no significant effect on purchasing decisions, Store Atmosphere had a significant effect on purchasing decisions and Experiential marketing and store atmosphere had a significant effect on purchasing decisions.

This study investigates the monetary transmission mechanisms influencing inflation and exchange rates across seven Southeast Asian countries (Myanmar, the Philippines, Indonesia, Malaysia, Singapore, Thailand, and Vietnam) over the period 2010–2023, with special focus on the impact of the COVID-19 pandemic. The research addresses the problem of macroeconomic instability, particularly the volatility in inflation and currency values during crisis periods, and aims to identify the dominant monetary factors affecting these indicators. The study employs a mixed quantitative approach using Structural Vector Autoregression (SVAR), Panel Autoregressive Distributed Lag (ARDL), and Paired Sample t-Test to analyze the short-term and long-term relationships among key variables: Gross Domestic Product (GDP), investment, money supply (M2), interest rates, inflation, and exchange rates. Findings reveal that GDP is the most influential factor impacting both inflation and exchange rates, followed by money supply and interest rates. The variance decomposition analysis confirms that these monetary variables significantly explain macroeconomic fluctuations in both pre- and post-pandemic contexts. The t-Test further indicates statistically significant changes in inflation and exchange rates before and after the pandemic, highlighting the disruptive effect of COVID-19 on economic stability. The results demonstrate that inflation declined significantly in most countries during the pandemic, while exchange rate behavior varied depending on economic resilience and policy responsiveness. The study concludes that maintaining macroeconomic stability requires not only monetary policy coordination but also effective public health crisis management. This research contributes to the regional policy discourse by offering empirical insights and evidence-based recommendations to strengthen economic resilience in Southeast Asia.

This study aims to explore the behavioral dynamics of Generation Z (Gen Z) toward digital culinary brands on TikTok, a platform increasingly central to youth consumer engagement. The research investigates how Gen Z interacts with, interprets, and forms relationships with culinary content in a digital environment shaped by algorithmic trends and participatory culture. Employing a qualitative phenomenological approach, data were collected through in-depth interviews with 12 Gen Z participants aged 18–24 years who actively engage with culinary brand content on TikTok. Additional data were obtained from observational analysis of brand-related content and user interactions on the platform. Thematic analysis revealed three core themes: emotional engagement with sensory-rich food content, digital consumption as identity performance, and expectations of brand authenticity and interactivity. Participants expressed strong affective responses to visually appealing and immersive content, linked their brand preferences to personal values and social identity, and favored brands that demonstrated responsiveness, humor, and human-like interaction. These findings highlight the role of TikTok not only as a marketing tool but as a cultural space where brand perception and loyalty are socially constructed. This study contributes to the theoretical understanding of consumer engagement by situating Gen Z’s behavior within a sociocultural and digital framework. Practically, it offers insights for culinary brands to develop more authentic, interactive, and value-driven content strategies. The findings also suggest implications for digital marketing policies and content regulation. Future research is recommended to explore cross-platform behaviors and cultural variations in digital brand engagement.

PT Unilever Indonesia’s strategic application is examined through the Balanced Scorecard framework, focusing on four key perspectives: financial, customer, internal business processes, and learning and growth. The analysis reveals that while the company demonstrates strong financial performance, such as high ROI and ROE, challenges like declining annual profits and increasing liabilities signal the need for improved cost management and risk mitigation. Unilever's strategy emphasizes innovation and customer relationships, leveraging Total Quality Management (TQM) and continuous product enhancements. However, internal issues such as employee work culture, inadequate facilities, and employee satisfaction remain significant obstacles to organizational performance. The findings suggest a need for stronger employee engagement and workplace improvements, alongside enhanced financial sustainability strategies. Future research could explore how external factors, such as shifting market trends and government regulations, influence Unilever’s strategic decisions and overall success.

This research is a case study with the object of research on Tenun Ikat Ina Sabu located at Jalan Sukun I, RT 009 / RW 004, Oepura Village, Maulafa District, Kupang City, East Nusa Tenggara. The purpose of this study was to determine and explain the production planning of Tenun Ikat Ina Sabu in Kupang City. The types of data used are qualitative and quantitative. Data collection techniques in this study were interviews, observations, questionnaires and documentation. While the data analysis techniques used are Linear Trend and Break Even Point (BEP). The results of the Linear Trend calculation show that in 2024 Tenun Ikat Ina Sabu will produce 383 pieces of sarong, 358 pieces of blanket and 284 pieces of shawl, then the amount produced for 2025, 414 pieces of sarong, 332 pieces of blanket and 303 pieces of shawl, and the amount produced for 2026, 445 pieces of sarong, 402 pieces of blanket and 322 pieces of shawl. The results of the Break Even Point (BEP) analysis in 2023 show that if Tenun Ikat Ina Sabu produces 1,060 pieces of ikat weaving or around Rp.90,343,129, then the company does not make a profit or loss.

Engine overheating is a critical condition that can cause damage to internal components, reduce operational efficiency, and lead to overall system failure. The absence of an automatic protection system is one of the primary factors contributing to damage. This study aims to design and test a temperature sensor-based safety device that can automatically cut off the engine's working system when the temperature exceeds the safe limit. The method used is descriptive statistical analysis to evaluate the effect of independent variables (operational time duration and workload) on the dependent variable (coolant temperature). The system was tested through water heating simulation using an electric heater and controlled by an Arduino Nano microcontroller, a MAX6675 temperature sensor. Testing was carried out with variations in power load (150, 300, 450, 600, and 750 Watts) and operational duration (20, 40, and 60 minutes). Temperature data were collected and analyzed using ANOVA to determine the effect of load and time on temperature increase. The results showed that the temperature increased significantly with increasing power load, with temperatures approaching 100°C at loads ≥450 Watts in less than 20 minutes. The load variable shows a significant effect on temperature (p < 0.05), while the duration of time shows a nonlinear but not statistically significant upward trend. The safety device is proven to be able to automatically disconnect the system when the temperature reaches the specified maximum limit, thus effectively preventing engine damage due to overheating.

Bitcoin is one of the most prominent digital assets in the modern financial era due to its high volatility and huge profit potential. However, its extreme price volatility also makes it a high-risk asset, so a reliable forecasting approach is needed to help investors make more rational decisions. This study aims to forecast Bitcoin price using the Moving Average (MA) method, specifically MA3, by utilizing monthly historical data of Bitcoin price in USD currency obtained from investing.com website. The MA3 method was chosen for its ability to smooth out short-term fluctuations and identify the direction of price trends. The forecasting process is performed by calculating the average of the last three months' prices for each point in time and compared to the actual price to evaluate its accuracy. The evaluation is done using various prediction error metrics, namely Error, Absolute Error, Squared Error, and Percentage Error. The results of the analysis show that the MA method provides a fairly representative picture of price trends and can be used as an early indicator in short-term investment strategies. Thus, the Moving Average method proves to be a simple but effective prediction tool, especially for novice investors in the dynamic crypto asset market.

Data from the Business Competition Supervisory Commission (KPPU) indicate that the impact of COVID-19 in 2020, 2021, and peaking in 2022 led to a significant increase in merger and acquisition (M&A) activities. This trend suggests that M&A actions have become an essential strategy for sustaining and enhancing business performance. However, not all M&A activities result in success, making it crucial to understand the factors influencing their outcomes. This study aims to examine and provide empirical evidence on the effect of board size, institutional ownership, and firm size on merger and acquisition performance. Agency theory and signaling theory are employed as the theoretical frameworks to explain the relationships between the independent and dependent variables. The population of this study consists of publicly listed companies that conducted mergers and acquisitions between 2019 and 2023. The sampling technique used was purposive sampling, resulting in a total of 150 samples. Data were collected through non-participant observation, and the data analysis technique applied was multiple linear regression. The results show that institutional ownership has a positive effect on merger and acquisition performance. In contrast, board size and firm size do not significantly influence M&A performance. These findings indicate that monitoring by institutional shareholders can enhance the effectiveness of strategic decision-making, while a larger organizational structure and firm size do not necessarily support post-merger integration success.

Shrimp petis is a traditional Indonesian fermented product that is susceptible to contamination by pathogenic bacteria such as Staphylococcus aureus, Escherichia coli, and Pseudomonas spp. Preservation is generally carried out with chemical antibiotics, but their use can cause side effects and microbial resistance. This study aims to examine the effectiveness of ginger extract (Zingiber officinale) as a natural antibiotic against bacteria in shrimp petis. Ginger extract is known to contain active compounds such as gingerol and shogaol which have antibacterial activity. Through literature studies and disc diffusion method analysis, it was found that ginger extract was able to produce an inhibition zone of 12–22 mm against test bacteria. These results indicate that ginger extract is effective in inhibiting the growth of pathogenic bacteria and has the potential to be used as a natural preservative. In addition, a combination of biological, chemical, and natural preservation approaches is recommended to maintain the quality and safety of shrimp petis. The use of ginger extract is in line with the trend of healthy and environmentally friendly food.

This study is based on the results of initial observations that indicate a downward trend in the number of non-JKN outpatients. In January 2024, the achievement was only 415 of the target of 596 visits (69.6%), the achievement was again not in accordance with the target in September with 92.8%. The purpose of this study was to examine the effect of psychological factors and social factors on patient decisions to visit with brand image as an intervening variable in outpatients at Hermina Hospital, Depok. This type of research is quantitative with a causality design. The population is outpatients at Hermina Hospital, Depok. The results of the distribution through questionnaires obtained 130 respondents according to the minimum sample set. The analysis technique used the three box method analysis and SEM-PLS. The results of the study showed that psychological factors, social factors, and brand image simultaneously had a significant effect on patients' visit decisions, with a contribution of 67.8%. Both psychological and social factors influenced brand image and patients' visit decisions. Brand image also had an effect on patients' visit decisions. Among the three variables, brand image was the most dominant in increasing patients' visit decisions.

This study ais to formulate development strategies for Yoga Barbershop in Palaran, East Kalimantan, using SWOT analysis and the Quantitative Strategic Planning Matrix (QSPM). SWOT analysis is utilized to assess internal and external factors,combned with QSPM to determine priority strategies. The study reveals that Yoga Barbershop’s strengths nclude customer loyalty, a strategic location, modern haircut styles,and ownership of the business premises, which reduces operational costs.However, identified weaknesses consist of limited service facilities, inflexible operating hours, restricted space, noise issues, and insufficient staff. Meanwhile, opportunities for Yoga Barbershop include opening new braches and recruiting additional employees. Threats arise from similiar business competitors and changes in hairstyle trends. Based on the findings, Yoga Barbershop’s IE matrix places the business in quadrant V, with a total IFE score of 2,72 and an EFE score of 2,71, indicating a stable position that requires stability strategies. The recommended strategy is the weakness-opportunity (WO) approach. Priority strategic recommendations, in order of importance, are opening a new branch, training new staff, and increasing the flexibility of operational hours.

The automotive industry is a strategic sector that plays a crucial role in national economic growth. Facing rapid digital transformation, automotive companies are increasingly adopting Business Intelligence (BI) systems to facilitate a data-oriented decision-making process. This study aims to explore the implementation of BI in XYZ, one of Indonesia’s largest car manufacturers. Using a descriptive qualitative approach through literature review, the research highlights how BI dashboards enable real-time analysis of vehicle sales trends, regional performance, and product models. The findings indicate that BI significantly enhances strategic planning, marketing accuracy, and operational efficiency. Visual tools such as Tableau provide centralized dashboards that facilitate faster insights, enabling companies to adjust production and distribution strategies based on data patterns. The study concludes that BI is not merely a visualization tool but a vital element of the digital transformation strategy in the automotive sector.