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This research aims to analyze the influence of e-commerce and financial technology on income inequality in Indonesia. This research uses panel data from 10 provinces in Indonesia in the 2018-2022 period. This research uses a panel random effect model (REM) regression approach with a GLS (generalized least square) estimation tool. The estimation results from this research show that e-commerce has a negative and significant effect on income inequality in Indonesia. Meanwhile, financial technology has a positive and significant effect on income inequality in Indonesia. It is hoped that the results of this research can be used as consideration for the government in making policies in an effort to reduce income inequality in Indonesia.  

Increasingly advanced technology currently encourages people to make transactions using electronic money (e-money). Currently, more and more Indonesia people are using electronic money, this can be seen from the volume of electronic money transactions which is increasing from year to year. People prefer to make transactions using electronic money because it is easier to transact with traders. This research aims to analyse the variables of interest rates, inflation, money supply, e-money and electronic money transactions in Indonesia. The type of research is quantitative analysis using secondary data from 2011 to 2021 with quarterly annual data take from Bank Indonesia (BI), World Bank and BPS (Central Statistics Agency). The analysis method used is VAR (Vector Autoregressive) and refined with Forecast Error Variance Decomposition (FEVD) analysis. The results of the VAR analysis show that there is a contribution to the variable itself and other variable. From the estimation results, it turns out that there is a reciprocal relationship between one variable and another variable, or in other words, all variable, namely the variable Inflation, JUB, E-Money, Interest Rate and Elecronic Money Transaction contribute to each other. The results of the FEVD analysis show that not all variables contribute to the variable itself.

This study aims to determine the effect of profitability, company size and capital structure on price to book value in banking companies. The research method used is quantitative research. The sampling technique used is using purpose sampling technique. Data analysis using Eviews 12 software and testing is carried out, namely data analysis methods (descriptive), regression model estimation methods, panel data selection, Multiple Linear Regression Analysis, and hypothesis testing. The results show that 1) there is no effect of profitability on price to book value. 2) there is an influence and significant company size on price to book value. 3) there is an influence and significant capital structure on price to book value. 4) the existence of independent variables simultaneously influence and significant to the dependent variable.    

PT Swadaya Graha is a company that works in the field of construction, fabrication and steel manufacturing. One of the machines used in carrying out its operational activities is the Baoji 1660A lathe. The lathe often fails during the production process. This study aims to determine critical components, critical component reliability values, maintenance scheduling intervals and maintenance cost estimates of the Baoji 1660A lathe using the Reliability Centered Maintenance (RCM) method. The results of this study show that the electrical system with an RPN value of 240, v-belt with an RPN value of 168, and gearbox with an RPN value of 60 as critical components. The reliability value of the electrical system approaches 0.5 at a time interval of 640 hours or 80 working days, the reliability value of the v-belt approaches 0.5 at a time interval of 208 hours or 26 working days, and the reliability value of the gearbox approaches 0.5 at a time interval of 384 hours or 48 working days. From the scheduling interval, the estimated total maintenance cost in 2025 is IDR 7,019,092, in 2026 is IDR 3,615,386, in 2027 is IDR 4,187,484, in 2028 is IDR 4,276,752, and in 2029 is IDR 3,615,386.

This study aims to analyze the effect ofproduct innovation and product quality partially and simultaneously oncompetitive advantage at Batak Restaurant inAlam Barajo District, Jambi City. Thisresearch uses a descriptive quantitative approach. The sampling method uses the Structural Equation Model method and uses Maximum Likehood Estimation (MLE). The sample inthis study were consumers at Batak Restaurant in Alam Barajo District, Jambi City, totaling 98 respondents. The data collected using a questionnaire withan ordinal scale. The data analysis method in this study usedSPSS version 25.0 software. The results ofthe study prove that Product Innovation and Product Quality have a significant effect simultaneously on Competitive Advantage, Product Innovation has a significant effect partially on competitive advantage and Product Quality has a partial effect on Competitive Advantage at Batak Restaurant in Alam Barajo District, Jambi City. The product quality variable is the most dominant variable affecting competitive advantage in Batak Restaurant in Alam Barajo District, Jambi City.    

In order to better understand the complex links between infrastructure development, education, tourism, agriculture, and regional economic growth in Indonesia, this study uses structural equation modeling with partial least squares, or SEM-PLS. The research makes use of a 287-observation dataset and applies rigorous measurement model evaluation, bootstrapping analysis, structural model estimation, and model validation against multiple fit indices. The results show a strong positive correlation between each sector—agriculture, tourism, education, and infrastructure development—and regional economic expansion. The necessity for comprehensive, integrated development strategies is highlighted by the interconnectedness of these interactions. In order to promote balanced and resilient regional economic growth, the findings provide policymakers with useful insights and highlight the significance of ongoing investments in infrastructure, education, and sustainable tourism and agricultural practices.    

Predicting sales is an important aspect in sales development. Sales prediction simulation is an estimated calculation of the level of product sales in a certain period. Sales of pempers tend to fluctuate due to the choice of many brands available, resulting in sales having a little difficulty in estimating sales of MAKUKU diaper products at Greens Mart stores. This research aims to predict sales Pempers products. This research uses several stages of identifying problems, determining research objectives, collecting data, data collected or obtained from interviews with salespeople, managing data using Monte Carlo stages, implementing/testing data and testing results to see the accuracy of the method used. The analysis results show that Comfit M and Comfit L have almost the same level of accuracy, namely Comfit M is around 90.63% and sales of Comfit L are 90.48%. These values ​​provide an indication of the level of accuracy of the sales predictions made.      

This research aims to analyze the influence of the labor force, inflation, unemployment and poverty on economic growth in Indonesia for the period (2014-2022). The variables used are Inflation as the dependent variable, Money Supply (JUB) and Interest Rates as the independent variables. The data used in this research is secondary data obtained from publications by the Indonesian Central Bureau of Statistics. The analytical method used is a multiple linear regression model or Ordinary Least Square (OLS). In processing the data, the author used the help of Eviews 10 software. Based on the estimation results, it was found that there is a relationship between Labor Force, Inflation, Unemployment and Poverty on economic growth in Indonesia and the variables Labor Force, Inflation, Unemployment and Poverty have a positive and significant effect on Economic Growth in Indonesia .      

Universities' development hinges significantly on student admissions, necessitating accurate predictions for effective planning. This study applies the Monte Carlo simulation method to forecast new student arrivals at the Faculty of Mathematics and Natural Sciences (FMIPA) at Universitas Negeri Medan (UNIMED). Utilizing data from 2021 to 2023 sourced from the PDDikti website, the research employs PHP programming for implementation. The Monte Carlo algorithm's numerical prowess ensures precise statistical data simulation, comprising data collection, probabilistic distribution computations, cumulative distribution determinations, random number generation, and simulation analyses. Simulation results for 2022, 2023, and 2024 exhibit consistent trends, projecting an average of 860 to 930 new students per program. This methodology surpasses manual estimations, offering robust insights for university resource allocation and strategic management. Despite its effectiveness, study limitations, such as model assumptions, warrant continuous validation with actual data. This research advances predictive modeling in higher education, providing a foundation for future enhancements and comprehensive prediction integrations.

This research applies the Monte Carlo simulation method to predict the movement of Apple Inc.'s stock price over a long period of time. Using historical data of Apple's stock price from 12 December 1980 to 24 March 2022, this study aims to generate a probability distribution of the future stock price. The method involves several steps, including data collection, log return calculation, parameter estimation, and simulation of the stock price path through random iterations based on the log return distribution. The simulation results show that the closing price of Apple stock can be predicted by following the historical trend, although there are differences with the real data due to the stochastic nature of the Monte Carlo technique. This research also applies a variance reduction method to improve simulation efficiency. The findings provide a valuable perspective for investors and financial analysts in identifying investment risks and opportunities through an in-depth understanding of the dynamics of stock price movements using Monte Carlo simulation. Suggestions for future research include the use of VaR methods with historical variance and covariance approaches, as well as considering longer data periods and more stock indices for more comprehensive results.

This research aims to analyze the influence of the Money Supply (JUB) and interest rates on inflation in Indonesia in the 2014-2023 period. The variables used are Inflation as the dependent variable, Money Supply (JUB) and Interest Rates as the independent variables. The data used in this research is secondary data obtained from publications by the Indonesian Central Bureau of Statistics. The analytical method used is a multiple linear regression model or Ordinary Least Square (OLS). In processing the data, the author used the help of Eviews 10 software. Based on the estimation results, it was found that there is a relationship between the Money Supply and Inflation in Indonesia and the Interest Rate variable has a positive and significant effect on Inflation in Indonesia.

Sari Buah Blimbing Wuluh MSMEs is one of the businesses engaged in food and beverage processing with the basic ingredients of star fruit. MSMEs Sari Buah Blimbing Wuluh has a problem in determining COGS which still uses the estimation method only. The purpose of this study was to identify the cost of production activities using the Full Cousting method. The method used in this research is deductive qualitative with data collection techniques through observation and interviews. The results showed that there was a price difference of Rp. 398 per bottle, with the calculation of COGS according to MSMEs amounting to Rp. 2,917 per bottle. While the calculation according to the full costing method is Rp. 3,315. This price difference occurs because business owners do not take into account direct labor costs, fixed factory overhead costs, variable costs, and non-production costs. So that the calculations made by MSMEs owners are not optimal for maximizing business profits.

A new, economical, sensitive, simple, rapid UV spectrophotometric method has been developed for the estimation of Acyclovir in pure form and pharmaceutical formulation. This UV method was developed using NaOH (0.1N) as a solvent. In the present method, the wavelength selected for analysis was 253nm. Using 1cm match quartz cells, all of the spectrum and absorbance measurements were performed using an UV-VIS spectrophotometer (Shimadzu 1800) was used to carry out the spectral analysis. The ICH guidelines were used to validate the method. Throughout the study, we compared the purity of the drugs, with standard drugs (HPLC grade purity >99%) purchased from SIGMA ALDRICH Ltd. The test drugs from pharmaceutical companies (CIPLA) in its dosage form taken from the market.The method was validated for linearity, range, accuracy, precision, drug content , LOD and LOQ. Linearity was found in the range of 2.5-40μg/ml. Accuracy was performed by using a recovery study. The percentage recovery for all the methods performed was in the range of 99-100% indicating of zero interference of the excipients (in the formulation).   LOD and LOQ were found to be 1.5766434 and 4.7777075 respectively [SD: 0.474474135; SE: 0.212191284]. Relative error (<2) values showed that the proposed procedure exhibited excellent Interday and intraday precision.The proposed UV spectroscopic method was found to be accurate, precise, stable, linear, specific, and simple for quantitative estimation of acyclovir in bulk and pharmaceutical dosage form. Hence the present UV spectroscopic method is suitable for the routine assay of acyclovir in bulk and pharmaceutical formulations.

This paper presents a comparative analysis of various battery management systems (BMS) in electric vehicles, with a focus on incorporating machine learning techniques to improve battery safety and extend battery life. The study evaluates conventional BMS against machine learning-enhanced models in predicting thermal runaway, state of charge (SOC), and state of health (SOH) under diverse operating conditions. Results indicate that machine learning algorithms outperform conventional methods, providing more accurate SOC and SOH estimations, thus enhancing vehicle safety and longevity.

The aim of the research is to evaluate the effect of using non-cash payment instruments on the demand for currency in Indonesia. Time series data is used in the time period 2009 to 2023 with monthly observations. The analysis approach uses the Error Correction Model (ECM) to assess the correlation between variables in the short and long term. The estimation results confirm that the use of ATM/debit cards has a positive and significant impact on the need for currency, both in the short and long term. In contrast, credit card use shows a negative and significant impact on the need for currency in both time periods. Meanwhile, the use of e-money does not have an impact in the short term, but has a positive impact in the long term on the need for paper money in Indonesia. Therefore, this research suggests that Bank Indonesia should encourage more use of electronic payment tools to encourage people to reduce the use of currency, and promote the concept of a society that uses less cash (less cash society).

The minimum wage is very effective as a tool to reduce income inequality. Apart from limiting the minimum wage in general, this policy also has an effect on increasing income and plays an important role in overcoming income gaps. Apart from the minimum wage, micro-spending also influences income inequality. This research aims to determine and analyze the influence of minimum wages and micro expenditure on regional income in Indonesia. This research uses multiple linear regression analysis. The data used is secondary data for 1 period, namely 2022, obtained from the Central Statistics Agency. The variables used are Regional Income (Y), Minimum Wage (X1), Micro Expenditures (X2). The classic assumption test uses the SPSS for Windows version 25 program. The estimation results show that the provincial Minimum wages affect poverty in Indonesia, education affects poverty in Indonesia, and health affects poverty in Indonesia. Local minimum wages, education, and health influence poverty in Indonesia.

This research explores the application of Monte Carlo Simulation in estimating portfolio risk in the Indonesian stock market. The primary objective is to assess the effectiveness of this method in predicting portfolio return distribution and managing risk compared to traditional methods like Value at Risk (VaR). Data from the Indonesia Stock Exchange (IDX) were used to analyze stock returns, focusing on sectors such as telecommunications and property. Monte Carlo Simulation was applied to generate multiple scenarios of stock returns based on historical data and probabilistic distributions. The findings show that Monte Carlo Simulation provides a more comprehensive risk estimation, especially for stocks with high volatility and small market capitalization. Unlike VaR, which assumes a normal distribution, Monte Carlo Simulation accounts for extreme risk events and market uncertainties. The study also highlights the importance of diversification, as portfolios with a mix of high and low volatility stocks demonstrate a more stable risk profile. The results suggest that Monte Carlo Simulation is an effective tool for investors looking to manage risk in dynamic market conditions, providing more accurate and reliable estimations compared to traditional risk assessment methods. This research recommends further exploration of Monte Carlo Simulation in other sectors or with varied data for broader applications in risk management.

The factors that influence students' motivation to participate in extracurricular activities are the focus of this study. These factors may originate within the student (internal factors) or from without (external factors). Students' needs, hopes, and interests are all internal factors that can influence their interest in and participation in extracurricular activities. However, external factors include things like family, the natural world, and social equilibrium.This study aims to shed light on the most influential factors influencing grade eight students' decision to participate in extracurricular activities. This study combines descriptive methods with quantitative estimation. Data collection software that makes use of angkets. This study's sample population consists of the sixty-five students that participated in the pre-exam activities at Class VIII of MTsN 2 in Pasaman Barat. This study used a non-probabilistic sampling technique called "total sampling," in which the entire population was sampled because the study's population was less than 100. This study used SPSS to conduct a thorough validity test, replicability test, normality test, homogeneity test, and factor analysis on the collected data. The research results show that the factors that influence students' motivation to participate in pramuka activities at the eighth grade level at MTsN 2 Pasaman Barat are as follows: the first factor is students' expectations, with an eigen value of 4.532, or 20.601%; the second factor is students' family environments, with an eigen value of 2,453, or 11.150%; and the third factor is students' school environments, with an eigen value of 4.532. That's why hope is the most important of those other twelve factors.    

Companies must struggle to survive and be the best, this encourages companies to use various strategies and innovations to prevent bankruptcy in the laws of law there are gaps that can be utilized by taxpayers to reduce the tax burden that must be paid. One of them is tax avoidance. The purpose of this study is to determine the effect and explain profitability, leverage on tax avoidance with sales growth as moderation variables in consumer goods companies listed on the Indonesia Stock Exchange for 2020-2021. Types of research approaches are quantitative, with a population of 4 companies and 32 data samples The quarterly financial uses using purposive sampling for sample determination. Data analysis techniques conducted with descriptive statistical analysis, testing of panel data regression estimation models, classical assumption tests, multiple linear analysis, t-test, and moderation regression analysis. The results of this study were obtained that the partial profitability variable had a significant effect on tax avoidance and partially leverage had no significant effect on tax avoidance. The results of moderation regression analysis obtained by the results of sales growth instead of the moderation variable between profitability and leverage of tax avoidance.

Examining the production costs employed by PT. Lasting Prosperous Industry is the aim of this study. The research approach used in this study was qualitative research methodology. The population and sample of the study were selected to represent the societal issues that the PT firm deals with. Langgeng Makmur Industri uses field research, including observation, interviews, and documentation, as well as library research. The results of the investigation show that PT. Langgeng Makmur Industri's production cost approach does not fully utilize current theory; yet, because the company levies a 3% reserve fee, the estimation procedure is nevertheless regarded as normal.