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This study aims to analyze the effect of renewable energy, energy consumption, and Gross Domestic Product (GDP) per capita on carbon dioxide (CO2) emissions in Indonesia for the period 1995-2024. This study uses secondary data over time (time series) with the Ordinary Least Square (OLS) multiple linear regression analysis method corrected using the Newey-West Heteroskedasticity and Autocorrelation Consistent (HAC) approach. The results show that renewable energy does not have a significant effect on CO2 emissions, which is caused by the still low share of renewable energy in the national energy mix which only reaches 10.95% in 2024. Energy consumption has a positive and significant effect on CO2 emissions, where every 1% increase in energy consumption increases CO2 emissions by 84.23%. Gross Domestic Product (GDP) per capita has a positive and significant effect on CO2 emissions. Every 1% increase in GDP per capita increases CO2 emissions by 35.03%, indicating that Indonesia remains on the EKC curve. Simultaneously, all three variables have a significant effect, with an adjusted R-squared value of 53.63%. This finding confirms that Indonesia's energy mix, still dominated by fossil fuels, is a major factor in high carbon emissions. Comprehensive energy efficiency policies, accelerated renewable energy transitions, and greener and more sustainable economic growth strategies are needed.

This research investigates how profitability, leverage, activity levels, and company scale impact financial distress in property and real estate firms traded on the Indonesia Stock Exchange. The selection of this sector stems from its high exposure to economic ups and downs, leaving its businesses particularly prone to financial troubles. Independent factors in the analysis include profitability, leverage, activity, and firm size, with financial distress serving as the outcome variable. Samples were drawn via purposive sampling from property and real estate entities listed on the Indonesia Stock Exchange over the 2022–2024 timeframe. Adopting a quantitative design, the study applies multiple linear regression as its core analytical tool. STATA version 17 handled the data analysis. Results show that, taken together, the independent variables exert a significant impact on financial distress. Ultimately, firms should optimize their financial metrics and pursue business growth to mitigate financial distress risks.

This study aims to examine the simultaneous and partial effects of the work environment and work-life balance on employee work stress at Hotel X. The research design is causal quantitative, with multiple linear regression analysis using SPSS 26.0 for Windows. The sample was obtained through purposive sampling (non-probability) of 120 respondents. The research subjects were employees working in shifts. The analysis results show that, (1) both variables simultaneously have a negative and significant effect on work stress, (2) the work environment has a negative and significant effect (sig. 0.002), and (3) work-life balance has a negative and significant effect (sig. 0.000). The work-life balance variable dominates its influence compared to the work environment, as seen from the lower significance value. These findings confirm that improving work-life balance and the work environment effectively reduces stress, especially for shift workers who are vulnerable to time imbalance. Based on the results, organizations are advised to optimize human resource management by maintaining a balance between job demands and employee conditions, as well as ensuring a proportional workload. Improvement in work-life balance can be achieved through flexible leave policies, adequate breaks between shifts, no overtime days except in emergencies, and minimizing personal time interruptions. These steps are expected to enhance employee well-being, retention, and productivity in the hospitality sector. Further research is recommended to explore different variables and methods, including comparing non-shift employees with the same variables, for more comprehensive insights.

This study evaluates how macroeconomic variables such as interest rates, inflation, and exchange rates affect the returns on corporate bonds issued by the banking sector in Indonesia. Corporate bonds are an attractive investment alternative, but their performance is highly influenced by fluctuations in national economic conditions. This study uses secondary data obtained from company financial reports, macroeconomic data, and bond market information over a certain period. Multiple linear regression analysis is applied to assess the extent to which each factor affects bond returns. The analysis results indicate that increases in interest rates and inflation tend to reduce bond returns, while the effect of exchange rates is inconsistent and depends on the economic stability at the time. These findings can serve as important considerations for investors, financial analysts, and policymakers in managing risks and opportunities in the Indonesia banking bondmarket.

This study aims to analyze the effect of product bundling strategies, countdown timer urgency, and social proof on the interactive responses of Generation Alpha consumers toward Scora skincare products in Bandar Lampung, with live streaming as a moderating variable. Interactive responses in this study include comments, questions, likes, and purchase actions during live streaming sessions. This research employs a quantitative approach, with data collected through ques-tionnaires. The sample consists of 300 Generation Alpha respondents in Bandar Lampung who have watched Scora’s live streaming promotions. Data analysis techniques include multiple linear regression analysis and Moderated Regression Analysis (MRA). The results indicate that product bundling strategies, countdown timer urgency, and social proof have a positive and significant effect on interactive responses, both partially and simultaneously. However, the moderation test results reveal that live streaming does not moderate the relationship between product bundling strategies, countdown timer urgency, and social proof on interactive responses. These findings suggest that although live streaming serves as a primary promotional medium, it does not necessarily strengthen the influence of marketing strategies on Generation Alpha’s in-teractive responses. This study is expected to provide practical insights for local skincare brands in developing more effective digital marketing strategies through live streaming commerce.

This research is motivated by the problem of the open unemployment rate in Maluku Province which is still fluctuating, where the influence of human capital indicators such as the Average Years of Schooling and the Gross Enrollment Rate of Senior High Schools as well as economic policies such as the Provincial Minimum Wage often show results inconsistent with theory, thus requiring further empirical studies to determine their influence in the region. The purpose of this study is to analyze and determine the partial and simultaneous effects of the average years of schooling, the gross enrollment rate of senior high schools, and the provincial minimum wage on the open unemployment rate in Maluku Province. The method used is quantitative with secondary data in the form of time series from 2015 to 2024 sourced from the Central Statistics Agency (BPS) of Maluku Province, and analyzed using multiple linear regression techniques. The results show that the average years of schooling have a negative and significant effect, while the gross enrollment rate of senior high schools and the provincial minimum wage each have a positive insignificant and negative insignificant effect on the open unemployment rate. Simultaneously, the three variables also have no significant effect. The implications of these findings confirm that increasing the average length of schooling is a key factor in reducing unemployment, but policies related to minimum wages and high school participation need to be reviewed and combined with other policies to be more effective in addressing unemployment in Maluku Province.  

The retail industry is currently facing increasingly intense competition, requiring optimal supply chain efficiency. Warehouses play a strategic role in controlling inventory flows and supporting a company’s operational performance. At K3Mart, stock shortages are still frequently found, caused by low supplier compliance with Service Level Agreements (SLA) and delays in delivery schedules, which negatively affect distribution processes and store service quality. This study aims to analyze the effect of supplier compliance with SLA and delivery timeliness on warehouse operational performance at K3Mart. This research employs a quantitative method by distributing questionnaires to 40 respondents from the warehouse, purchasing, and procurement divisions using a saturated sampling technique. The research instrument uses a Likert scale. Data analysis was conducted using validity and reliability tests, classical assumption tests, multiple linear regression analysis, t-test, F-test, and coefficient of determination with the assistance of SPSS software. The results show that supplier compliance with SLA and delivery timeliness have a positive and significant effect, both partially and simultaneously, on warehouse operational performance. Therefore, improving supplier compliance with SLA and delivery timeliness can enhance optimal warehouse operational performance.

This study aims to analyze the quality of room attendant service based on Standard Operating Procedures (SOPs) at the Lorin Solo Hotel and identify factors influencing its implementation. The research method used a qualitative approach through interviews, observations, and analysis of guest reviews.The results indicate that the implementation of SOPs has been successful, particularly in terms of room cleanliness, linen changes, replenishment of amenities, checking facilities, and friendly service. However, during periods of high occupancy, obstacles were encountered such as limited staff, limited cleaning time, and delays in replenishing amenities. Internal factors (skills, training, work motivation) and external factors (occupancy rate, guest demand, facility condition) influence service quality.This study concludes that the implementation of SOPs at the Lorin Solo Hotel has been successful, but needs improvement in time management, additional staff during busy periods, and regular training to maintain consistent service quality. These recommendations are expected to help the hotel improve service standards and maintain guest satisfaction.

This study aims to analyze the influence of interest rates, exchange rates, and coffee production on the value of coffee exports in South Sulawesi. The background of this study is based on the condition of South Sulawesi coffee exports which have experienced significant fluctuations in recent years despite coffee production tending to increase. This study uses a quantitative approach with time series data for the period 2009-2023 sourced from the World Bank, International Monetary Fund and the Directorate General of Plantations, the Food Crops, Horticulture and Plantation Service of South Sulawesi Province. Data analysis was conducted using multiple linear regression through the EViews 12 application with the classical assumption test as a model prerequisite. The results show that partially interest rates have a significant effect on coffee exports, while exchange rates and coffee production do not have a significant effect. Simultaneously, the three independent variables do not have a significant effect on the value of coffee exports. This finding indicates that external factors, especially interest rates, are more dominant in determining the performance of South Sulawesi coffee exports than internal factors of production and exchange rates.

The rapid growth of e-commerce has intensified the need to understand transaction patterns and customer purchasing behavior as a foundation for strategic decision-making. This study aims to analyze e-commerce transaction patterns and customer purchasing behavior based on demographic characteristics and transaction timing. By utilizing e-commerce transaction data, this research seeks to provide a more comprehensive understanding of customers’ purchasing tendencies and the factors influencing their behavior. This study employs Exploratory Data Analysis (EDA) as the primary method to descriptively explore data characteristics through various statistical visualizations, including histograms, bar charts, line graphs, and boxplots. The analysis conducted to identify transaction trends, the distribution of purchase values, and behavioral differences across demographic groups and specific time periods. The results indicate that e-commerce transaction patterns tend to increase during certain periods, particularly in the latter part of the observation timeframe, suggesting the influence of seasonal factors and promotional strategies. The distribution of transaction values is asymmetric, with most transactions occurring in the low to medium value range, while high-value transactions are conducted by a relatively small proportion of customers. Furthermore, variations in purchasing behavior are observed across demographic groups in terms of transaction frequency and value, despite relatively balanced transaction volumes. The findings confirm that e-commerce customer purchasing behavior is influenced by a combination of temporal factors and demographic characteristics. These results are expected to serve as a basis for e-commerce practitioners in developing more targeted marketing strategies and as a reference for future research in the field of e-commerce data analytics.

The rapid development of digital technology, especially after the COVID-19 pandemic, has brought changes to people's behavior and lifestyle with the trend of digital payments. One of the advances in digital financial services technology is PayLater, a Fintech innovation that offers easy transactions in the form of loans and installments without a credit card. This study aims to analyze the influence of transaction convenience and risk perception on purchasing decisions using the PayLater feature on e-commerce platforms among Generation Z in Samarinda City. This study uses a quantitative approach with associative methods and multiple linear regression analysis using SPSS 27. The method used is purposive sampling to obtain a sample of 100 respondents from Generation Z in Samarinda City, aged 18-28 years, who have used PayLater on e-commerce platforms. The findings show that transaction convenience (X1) has a positive and significant effect on purchasing decisions, but risk perception (X2) does not have a significant effect on purchasing decisions. At the same time, both variables have a significant effect on purchasing decisions. The findings of this study are expected to provide valuable insights for the PayLater feature to design more effective strategies to improve customer satisfaction and transaction experience.

This study aims to examine the influence of investment, labor, and unemployment rates on economic growth in Aceh Province. Economic growth is one of the main indicators in assessing the success of a region's development, so it is important to understand the factors that can influence it. The data used in this study are secondary data in the form of annual data for the period 2009–2023 obtained from the Central Statistics Agency (BPS) of Aceh Province and several related institutions. Data analysis was conducted using the multiple linear regression method with a time series approach. The results of the analysis show that the investment variable has a positive and significant influence on economic growth in Aceh Province, indicating that increased investment can encourage increased regional economic output. The labor variable also has a positive influence on economic growth, although its significance is lower compared to investment. Meanwhile, the unemployment variable has a negative and significant influence on economic growth, which means that increasing unemployment rates can suppress the rate of economic growth in Aceh Province.

Rapid adoption of cashless payments has reshaped everyday spending, especially among young consumers. While e-wallets deliver speed and convenience, constant exposure to discounts, cashbacks, and one-click checkouts may also foster more frequent discretionary purchases. This study examines the relationship between e-wallet usage intensity and consumptive lifestyle, focusing on how convenience and promotional stimuli relate to spending tendencies. Using a cross-sectional online survey of students and early-career workers, we collected self-reports on payment habits and consumption patterns with validated Likert-type instruments. Data were screened and analyzed with correlation and linear regression after basic assumption checks. The results indicate a positive and statistically meaningful association between e-wallet usage and consumptive lifestyle; respondents who transact more often via e-wallets tend to report stronger preferences for instant gratification, hedonic purchases, and impulse buying. Convenience features (e.g., stored cards, fast checkout) and promotional exposure (e.g., limited-time deals) emerged as salient correlates of the relationship. The findings add contextual evidence from Indonesia’s digital economy and suggest practical implications for users, platforms, and educators. Financial-wellbeing interventions such as digital budgeting tips, in-app nudges, spend limits, or post-purchase reflections may help align seamless payments with healthier consumption decisions. Future work can test causal mechanisms and evaluate design features that encourage prudent, goal-consistent spending without diminishing user experience.

This study seeks to evaluate the extent to which profitability, leverage, independent commissioners, and political links influence tax avoidance in Indonesian mining companies for the 2021–2024 timeframe. The mining sector was chosen because it contributes significantly to national income but is typically associated with the practice of tax avoidance. The novelty of this study lies in the addition of the political connections variable, which has rarely been studied in the context of Indonesian mining. The research data were obtained from annual reports and financial statements of companies obtained through purposive sampling, resulting in 77 observations. Multiple linear regression analysis under a quantitative method was applied, and the evidence suggests that profitability contributes positively to tax avoidance, as higher profits are associated with a stronger tendency for companies to minimize tax payments. Conversely, political connections have a negative effect, indicating that political and military experience shapes loyalty to the interests of the state, thereby encouraging tax compliance. Meanwhile, leverage and independent commissioners do not exert any influence on tax avoidance. The outcomes of this research may serve as a reference for regulators, scholars, and investors to better comprehend the determinants of tax avoidance and to contribute to enhancing governance structures and refining tax policy.

Polusi udara partikulat halus (PM2,5) merupakan ancaman serius bagi kesehatan masyarakat di Kabupaten Brebes, Jawa Tengah. Faktor penyumbang utamanya adalah emisi kendaraan di jalur Pantura, aktivitas industri perikanan, serta konsentrasi tinggi selama musim kemarau (Juni–November). Tidak adanya model peramalan sub-jam yang akurat menghambat pengembangan sistem peringatan dini yang efektif. Penelitian ini mengembangkan dan mengevaluasi model deep learning berbasis Transformer untuk memprediksi konsentrasi PM2,5 dengan resolusi waktu 15 menit. Data yang digunakan berasal dari NASA GEOS-CF (band PM25_RH35_GCC) yang diakses melalui Google Earth Engine menggunakan API Python. Dataset mencakup periode 1 Januari hingga 22 November 2025, menghasilkan 7.813 observasi per jam, yang kemudian diinterpolasi linear menjadi 31.249 titik data dengan resolusi 15 menit. Arsitektur Transformer terdiri dari 3 lapis enkoder, 4 kepala perhatian multi-head, dimensi embedding 128, dimensi feed-forward 256, panjang sekuen 60 timestep, dan augmentasi fitur menggunakan rerata bergulir (*rolling mean*, jendela = 3) dan beda pertama (*first difference*). Pelatihan dilakukan dengan TensorFlow-Keras, pengoptimal Adam, penjadwal peluruhan kosinus (*cosine decay scheduler*), dan fungsi kerugian Huber. Pembagian data dilakukan secara kronologis: 70% pelatihan, 30% validasi. Evaluasi pada set uji independen (16 Agustus–21 November 2025, 9.357 observasi atau 97 hari 11 jam 15 menit) menghasilkan MAE 0,7691 µg/m³, RMSE 1,2052 µg/m³, R² 0,9945, dan *Explained Variance Score* 0,9948. Model ini mampu menggambarkan variasi diurnal dan anomali musiman secara akurat, jauh melampaui model LSTM dan GTWR konvensional. Penelitian ini memberikan kontribusi signifikan di bidang Teknologi Informasi melalui kerangka kerja pengolahan *big data* satelit untuk aplikasi lingkungan.

This study aims to determine the effect of information technology utilization on the timeliness of financial reporting in the Regional Apparatus Work Units (SKPD) of North Toraja Regency. The use of information technology is expected to enhance the effectiveness and efficiency of the financial reporting process so that reports can be prepared and submitted on time. However, variations in reporting timeliness among several SKPDs indicate the need for further examination of the extent to which information technology has been optimally utilized. The research method employed is a quantitative approach with a simple linear regression analysis technique. Data were collected through questionnaires distributed to financial staff of SKPDs in North Toraja Regency, with a total of 50 respondents. Data analysis was conducted using SPSS through validity testing, reliability testing, classical assumption testing, and hypothesis testing. The results of the study show that the utilization of information technology has a positive and significant effect on the timeliness of financial reporting. These findings highlight the importance of optimizing the use of information technology in supporting effective and timely financial reporting.

Games that were initially enjoyed individually and offline have now evolved into online games that allow interaction, competition, and friendship with other players in real-time. Online games are now increasingly popular, one of which is Mobile Legends. This game can be downloaded through the Play Store and App Store. In April 2024, Mobile Legends ranked the most popular game by downloads on the statista.com website. The research objective was to determine the influence of event marketing, content marketing, influencers, and the social environment on the decision to purchase Mobile Legends game skins in Kebumen Regency. The method used was non-probability sampling with a purposive sampling technique aimed at 100 users. Data collection techniques used questionnaires and literature studies. The data analysis technique used multiple linear regression, which was then processed with the SPSS application version 25.0 for Windows. The results showed that event marketing had a significant effect on purchasing decisions, content marketing had a significant effect on purchasing decisions, influencers had no significant effect on purchasing decisions, the social environment had no significant effect on purchasing decisions, and event marketing, content marketing, influencers, and the social environment simultaneously had a significant effect on purchasing decisions.

This study aims to analyze the effect of inflation, Gross Regional Domestic Product (GRDP), and the Provincial Minimum Wage (PMW) on the poverty line in 10 provinces in Indonesia. The research employs a quantitative approach using panel data regression analysis. The data utilized in this study consist of panel data covering a 10-year period, from 2015 to 2024, obtained from the Provincial Offices of Statistics and Statistics Indonesia (Badan Pusat Statistik/BPS). To examine the relationship between variables across regions and over time, the fixed effect model is applied in the analysis. The results of the analysis indicate that inflation and GRDP do not have a statistically significant effect on the poverty line in the 10 provinces examined. These findings suggest that although inflation and GRDP are important macroeconomic indicators, their variations during the study period were not sufficient to directly influence changes in the poverty line across the provinces. In contrast, the Provincial Minimum Wage (PMW) is found to have a significant effect on the poverty line. This result implies that increases in the minimum wage play a crucial role in improving household purchasing power, which can contribute to reducing poverty levels. Overall, the findings highlight the importance of wage policy as an effective instrument for poverty alleviation at the provincial level. While broader economic growth and price stability remain important, policies related to minimum wage determination appear to have a more direct and measurable impact on poverty conditions. Therefore, policymakers are encouraged to consider wage policies alongside other macroeconomic strategies to achieve more effective poverty reduction outcomes.

This study aims to analyze the effect of taxpayer compliance and taxpayer awareness on the obligation to pay individual income taxes in Tasikmadu District. Taxes are the primary source of state revenue; therefore, compliance and awareness play a crucial role in optimizing tax collection. However, the compliance level of individual taxpayers in Tasikmadu District remains suboptimal, as many taxpayers have not fulfilled their obligations accurately and on time. This research employed a quantitative approach with a survey method. The population consisted of individual taxpayers registered in Tasikmadu District, and a total of 400 respondents were selected using Slovin’s formula. Data were collected through questionnaires with a Likert scale and analyzed using validity and reliability tests, classical assumption tests, and multiple linear regression analysis with the assistance of statistical software. The results indicate that taxpayer compliance has a positive and significant effect on the obligation to pay taxes. Taxpayer awareness also shows a positive and significant effect. Simultaneously, compliance and awareness significantly influence individual tax obligations in Tasikmadu District. The adjusted R² value of 0.420 demonstrates that these two variables explain 42.0% of the variation in tax obligations, while the remaining 58.0% is influenced by other factors not examined in this study. Based on these findings, it is recommended that the Directorate General of Taxes improve tax education and socialization programs, as well as expand the use of technology-based tax services to strengthen taxpayer compliance and awareness. Strengthening these aspects is expected to enhance tax revenue optimization and support sustainable national development.

This study aims to analyze the effect of service quality on passenger satisfaction at Tingkir Bus Terminal, Salatiga City. Service quality is an essential factor in achieving customer satisfaction, especially in public transportation services that cater to the needs of the community. The study underscores the importance of efficient and reliable services in improving the overall passenger experience. This research uses a quantitative approach, employing a survey method with 100 respondents who are passengers at the terminal. Data were collected through a Likert-scale questionnaire, designed to measure various aspects of service quality such as timeliness, comfort, and customer support. The data were analyzed using SPSS version 26, with procedures including validity tests, reliability tests, simple linear regression, and hypothesis testing (t-test). The results show that service quality has a positive and significant effect on passenger satisfaction, suggesting that higher service quality leads to increased satisfaction. This finding emphasizes the critical role of service quality in enhancing the operational success of public transportation services. The study’s findings are expected to serve as valuable evaluation material for improving service quality and provide practical insights for terminal management to enhance passenger satisfaction in the future.