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This study aims to analyze the impact of Total Asset Turnover, Debt to Equity Ratio, Return on Equity, and Sales Growth on the Price to Book Value of the Property and Real Estate sub-sector listed on the Indonesia Stock Exchange (IDX) for the 2018–2022 period. This research is a quantitative study using purposive sampling to determine the sample, resulting in 50 companies out of 84. The analytical model employed is multiple linear regression. The results of this study indicate that Total Asset Turnover, Debt to Equity Ratio, and Sales Growth have a significant positive effect on Price to Book Value, while Return on Equity has no effect on Price to Book Value.

to determine the partial and simultaneous effects of NPM, DER, and EPS on the stock prices of manufacturing firms in the food and beverage industry. For this quantitative research, secondary data sources were the Food and Beverage Department Manufacturing Companies' Financial Statements published in the IDX. Purposive sampling is the technique used for sampling. The t-test, F-test, and multiple linear analysis tests were used in this study's testing. The results of the partial study (t-test) showed that the stock prices of food and beverage manufacturing companies listed on the Indonesia Stock Exchange were positively and significantly impacted by NPM, DER, and EPS. It concurrently demonstrated that the stock prices of the Food and Beverage Manufacturing Companies listed on the IDX were positively and significantly impacted by NPM, DER, and EPS, either separately or in combination..

This study examines the effect of market risk, investor sentiment, and interest rates on the performance of energy sector stocks in Indonesia for the period 2019–2023, with market liquidity as a mediating variable. The study was conducted through a literature review by identifying and analyzing various related studies. Secondary data was obtained from scientific journals and related reports using relevant literature selection techniques. The results of the study indicate that oil price volatility, investor sentiment, and interest rate changes significantly affect the performance of energy sector stocks. Market liquidity was found to be able to reduce the negative impact of market risk and interest rates, and strengthen the positive influence of investor sentiment on stock prices. This study concludes that market liquidity plays an important buffer in maintaining the stability of stocks in the energy sector, especially in dealing with market fluctuations. The results of this study contribute to investment managers in developing more adaptive portfolio strategies and to regulators in creating policies that support market liquidity.

Profit emerges as a pivotal informational cornerstone captivating investor attention, adeptly revealing the intricate dynamics of a company's stock valuation. Through PBV, researchers can discern stock valuation via a rational and concise approach. The research aims to explore the correlation between profitability and stock price within telecommunication enterprises registered at BEI during the 2020-2022 period. Employing purposive sampling, the study selected 16 companies as analytical units. The research methodology implements a descriptive-verifiable approach, leveraging secondary data sourced from BEI. Statistical analysis proceeded through linear regression to uncover inter-variable relational patterns. Research findings demonstrate that profitability contributes significantly to stock price fluctuations, with a 20.6% influence at a moderate correlation level.

This research aims to examine the effect of the Debt to Equity Ratio (DER) on the stock value of PT. Ramayana Lestari Sentosa Tbk during the 2019-2023 period. Using quantitative analysis with dependent data obtained from the Indonesia Stock Exchange, the analysis shows that the company's DER was within a moderate range (35%-42%) throughout the study period. The results indicate a negative correlation between DER and stock prices; however, the effect is not significant when viewed partially. The decline in DER in 2023 reflects the company's efforts to strengthen its capital structure and reduce dependence on debt. These findings are expected to enhance investors' knowledge and support the company's operations in developing future financial and investment strategies.    

This study aims to analyze the effect of BI Rate, Rupiah exchange rate, and accounting profit on the Composite Stock Price Index (IHSG) in Indonesia. As one of the main indicators in the capital market, IHSG reflects the overall stock market performance and is influenced by various macro and micro economic factors. BI Rate as the reference interest rate, Rupiah exchange rate as an indicator of currency exchange rate, and accounting profit as a measure of company performance have high relevance to the movement of IHSG. This study uses a literature review method by referring to various previous studies that discuss the relationship between these variables. The results of the analysis show that the three variables have a significant influence on IHSG, both directly and indirectly. BI Rate and Rupiah exchange rate affect IHSG through financial market mechanisms, while accounting profit is more related to investment decisions and individual company performance. These findings provide insight for investors, policy makers, and academics to understand the dynamics of the relationship between economic indicators and stock market performance in Indonesia.

Hydroponic plant cultivation is booming, but stock and sales are hard to predict. Poor prediction can cause farmers to overstock and lose money. This study suggests a framework that uses several machine learning models, including Linear Regression (LR), Random Forest (RF), Decision Tree (DT), and Extreme Gradient Boosting. "Ensemble Learning," which combines these models, should yield more accurate and generalizable results than a single model. This framework is assessed using historical hydroponic plant sales data and related factors like price, weather, and market trends. The model's performance is measured by the difference between predictions and actual values using RMSE and MAE metrics. This framework should improve hydroponic plant stock and sales predictions. Farmers can make better production, inventory, and harvest distribution decisions. Besides reducing financial losses, this reduces food waste and improves food security.

The financial performance of mining companies listed on the Indonesia Stock Exchange (IDX) during the 2020-20203 period was greatly influenced by fluctuations in global commodity prices and macroeconomic conditions that had an impact on the company's competitiveness and profitability. Therefore, it is important to assess how companies in this sector are managing their financial performance amid various challenges and opportunities. This study analyzes financial performance using several main financial ratios, including liquidity ratios (Current Ratio and Quick Ratio), solvency ratios (Debt to Equity Ratio and Debt to Asset Ratio), profitability ratios (Return on Assets, Return on Equity, and Net Profit Margin), and activity ratios (Total Asset Turnover and Inventory Turnover). The method used to conduct the analysis is the quantitative descriptive analysis method, using data that has been taken based on the annual financial statements of companies listed on the IDX during the period. Sample selection using the purposive sampling method, resulted in 3 companies being analyzed. The results of the analysis of 81 data observed using the Multiple Linear Regression method showed that environmental performance and environmentally friendly products had a positive impact on the company's financial performance, while environmental poroscope and environmental activities did not show a significant influence on the company's financial performance.

In general, products that are bought and sold in the capital market are company ownership rights and company debt statements. Buyers in the capital market can be individuals, institutions or organizations who are willing to set aside funds to invest in the capital market. In securities trading transactions in the capital market, there are two forms of legal protection, namely, preventive legal protection and repressive legal protection through Law Number 8 of 1995 concerning Capital Markets and the connection with the existence of BAPEPDAM (Capital Market Supervisory Agency) which has changed its name to Authority. Financial Services (OJK). However, in practice there are still crimes involved, one of which is cornering the market The cause of cornering the market in the capital market begins with widening stock spreads and increasing share price volatility. However, the Capital Market Law still has weaknesses in terms of handling practices in the form of cornering the market, so it is still considered inadequate. And can optimize the imposition of prison sentences on perpetrators of cornering the market in the capital market as has been implemented by the United States.

When making investment decisions, it is crucial for investors to consider various risks that may arise, both in the short and long term. One method to measure risk is through volatility. Volatility represents a statistical measurement of the degree of price variation over a specific period, expressed as volatility (σ) (Aklimawati & Wahyudi, 2013). This study aims to discuss the pricing of European option contracts using Conditional Monte Carlo simulation and the Black-Scholes method. The data used in this study is secondary data obtained from Yahoo Finance. The data consists of quantitative information, namely the monthly closing prices of Toyota Motor Corporation (TM) stock, spanning 5 years from July 1, 2019, to July 1, 2024, yielding 60 data points. In this research, the pricing of European call option contracts was calculated using Conditional Monte Carlo simulation and the Black-Scholes method. The study concludes that European option contract pricing can be determined using two methods: Conditional Monte Carlo simulation and the Black-Scholes method. Conditional Monte Carlo simulation can be employed to calculate European option prices in a structured manner, utilizing stochastic volatility estimated through the Ordinary Least Squares (OLS) method. The two methods yield differing option prices; Conditional Monte Carlo simulation produces lower option price estimates with relatively lower error values compared to the Black-Scholes method at every strike price. The lower estimates from Conditional Monte Carlo simulation are due to its consideration of stochastic changes in volatility, whereas the Black-Scholes method results in higher prices due to its assumption of constant volatility. The comparison demonstrates that Conditional Monte Carlo simulation provides cheaper price estimates under market conditions with non-constant volatility, despite requiring higher computational time compared to the Black-Scholes method.   ,

Masita Wahyuni Asih 2024, The Effect of Non Performing Loan (NPL), Return on Asset (ROA), and Capital Adequacy Ratio (CAR) on Price to book value (PBV) at BUMN Banks listed on the Indonesia Stock Exchange for the 2018-2023 Period. Makassar STIM-LPI Management Science Study Program (supervised by Fausiah, S.E., M.Si. and Andi Herman Tellu, S.E., M.M.). The purpose of this study was to determine the effect of Non Performing Loan (NPL), Return on Asset (ROA), and Capital Adequacy Ratio (CAR) on Price to Book Value (PBV) at BUMN banks listed on the Indonesia Stock Exchange both partially and simultaneously. Price to Book Value (PBV) is the dependent variable (Y), and three independent variables (X) are used, namely Non Performing Loan (NPL), Return on Asset (ROA), and Capital Adequacy Ratio (CAR). Saturated sampling was used to obtain secondary data from a population of 4 banking companies listed on the Indonesia Stock Exchange. Descriptive statistics and classical assumptions, such as multicollinearity assumption and heteroscedasticity assumption, have been tested in relation to the research findings. The data analysis approach uses panel data regression, hypothesis testing, and the Fixed Effect Model (FEM) test. The partially tested study results show that while non-performing loans (NPLs) do not affect price to book value (PBV) significantly, there are return on assets (ROA) and capital adequacy ratio (CAR) that do. The findings of this study also simultaneously show that PBV is significantly affected by NPL, ROA, and CAR.

In the world of investment, there is a strong correlation between risk and return. An investor must be aware of the risks that arise and the expected rate of return. The rate represents the risk of betting on a particular stock; if the rate for the stock is marginal, it also represents the risk for the stock. The purpose of the reverse listing is to determine the effect of Stock Prices on Stock Returns. Reverse listing is a type of associative listing that uses a quantitative approach. The data used in the reverse listing is the latest stock price obtained from the official website of the Indonesian Stock Exchange (IDX). The population in the reverse listing is all companies listed on the LQ 45 Index from January 2022 to December 2022, totaling around 83 companies. The sample of the initial release is based on the criteria that have been set and used by approximately 10 companies. The initial release was carried out on all companies listed in the LQ 45 Index from January 2022 to December 2022, totaling approximately 83 companies. The initial release sample is based on the criteria that have been set and used by approximately 10 companies.

Examining how tax avoidance, company size, and financial performance affect stock values is the aim of this study. A thorough analysis of the 2021-2023 financial statements of infrastructure companies listed on Indonesia Stock Exchange (IDX) was conducted in order to support this study. Employing a purposive sampling methodology, the sample for this research comprised 22 infrastructure firms.Every selected entity that serves as a research sample provides the secondary data used in this study through its financial statement. To elucidate financial performance, this research utilized the following variables: Current Ratio (X1a), Debt-to-equity Ratio (X1b), Total Asset Turnover (X1c), Return on Equity (X1d), Price-earnings Ratio (X1e), and Company Size (X2) as the second independent variable, alongside Tax Avoidance (X3) as the third independent variable. The research methodology employed in this study was the panel data regression approach, utilizing the E-views 12 software to facilitate the analysis of the research outcomes. The result of the research suggest that the Random Effect Model (REM) constitutes the most efficacious analytical framework. Furthermore, the findings of the study reveal that, while the other variables did not exert an influence on stock price, both the Return-on-equity Ratio (X1d) and Company Size (X2) significantly impacted stock price.  

The chicken cartel in Indonesia that was exposed in 2016 has become a major issue affecting market structure and corporate competition. This strategy involves 12 large companies collaborating to control the availability and price of chicken by limiting chicken production (parent stock). Using a descriptive approach and normative legal research methods, this study examines how the cartel affects market structure, corporate competitiveness, and consumer welfare. This study reveals that the chicken cartel encourages oligopolistic conditions that are detrimental to small producers, consumers, and the economy as a whole. Large companies dominate the market, causing consumers to pay unfair prices, while small farmers lose their competitiveness.    

Transfer pricing is a policy used when setting the transfer price of a transaction, whether it involves goods, services, intangible assets, or financial transactions, and is often practiced in the industrial world. The practice of transfer pricing can be reflected in aspects of tax planning, bonus mechanisms, the valuation of intangible assets, and tunneling incentives. This study aims to examine whether tax planning, bonus mechanisms, the determination of intangible asset values, and tunneling incentives are variables that influence transfer pricing practices. The population in this study consists of 136 industries, and 80 samples were obtained from manufacturing companies listed on the Indonesia Stock Exchange for the period of 2018-2021. The sample selection was conducted using purposive sampling with the following criteria: 1) manufacturing companies listed on the Indonesia Stock Exchange during the period of 2018-2021, 2) companies that did not incur losses during the observation years, 3) companies that have special relationships in the form of sales transactions with related parties, and 4) companies that record intangible assets. This research uses panel data analysis techniques with the assistance of EViews 9 tools. The research results indicate that tax planning, intangible assets, and tunneling incentives have a significant positive effect on transfer pricing. Meanwhile, the mechanism of bonuses has a negative but insignificant effect on transfer pricing

This study comprehensively investigates the empirical impact of capital structure, profitability, and asset growth on the value of companies in the retail sector on the Indonesia Stock Exchange during the post-pandemic economic recovery phase (2021–2024). Adopting a quantitative methodology with purposive sampling of 12 entities (N=48), parameters were estimated using multiple linear regression after passing a rigorous classical assumption test including normality, multicollinearity, and heteroscedasticity. By proxiesizing the capital structure through Debt to Equity Ratio (DER), profitability through Return on Assets (ROA), and total asset growth to Price to Book Value (PBV), this study reveals the phenomenon of  market undervaluation with an average PBV of 0.17. The results of statistical tests confirm that these financial determinants partially and simultaneously have a significant influence on shaping the firm value. These findings provide a theoretical contribution regarding the relevance of funding policy and operational efficiency as crucial signals for investors in a volatile market landscape. The practical implications emphasize the importance of optimizing financial structure and operational performance to strengthen market confidence during the global economic transition period.

This study aims to determine and evaluate the Performance of the Food Crops Agriculture Service in the 2018-2023 Subsidized Fertilizer Distribution Program (Case Study of Rice Farmers, in Seso Village, Ngada Regency). Using a qualitative descriptive approach with Atik Septi Winarsih's theory and Robbins' theory which highlights Responsiveness, Responsibility, Accountability, Punctuality, Work Commitment. The study involved 12 Informants.The results showed that in the subsidized fertilizer distribution program, employees of the Food Crop Agriculture Office of Ngada Regency have not carried out their duties in accordance with the needs of farmers on agricultural land, this is due to communication deficiencies such as in terms of providing infrastructure, fertilizer stocks, and the problem of changing fertilizer price increases and in terms of special training in accessing the E-RDKK system. One of the factors that hinders access to this system is that farmers do not understand the use of the E-RDKK system through android phones and the lack of knowledge that farmers have. The Ngada Regency Food Crop Agriculture Office has also not provided sufficient facilities and infrastructure on farms because there are many delays in distribution that take more time than the specified time. Services at the Ngada Regency Food Crop Agriculture Office have not been in accordance with the implementation in the field so that farmers' needs have experienced delays in service. Another form of participation that supports the sustainability of the subsidized fertilizer distribution program is by conducting socialization activities. The form of participation that is carried out is contrary to community expectations where the completion time is delayed from the time that should be determined.

The purpose of this research is to analyze the correlation between capital structure, profitability, and stock market value, proxied by the price-to-book ratio. The capital structure variable is measured using DER, while profitability is measured using the ROA. In this study, the data used comes from the financial statements of property and real estate companies listed on the IDX during the period of 2020 to 2023. This study applies multiple linear regression analysis with the help of SPSS to process data obtained from 22 purposively selected companies over four years. The research concludes that capital structure and profitability are crucial factors that can influence stock prices. These results indicate that companies need to focus on improving profitability and maintaining healthy debt management to enhance their value in the eyes of investors. Additionally, investors should not rely solely on the PBV when evaluating investment prospects.

This study aims to examine the impact of NPM, ROI, and ROE on stock prices. The population of this research consists of infrastructure companies listed on the Indonesia Stock Exchange (IDX) during the period of 2019-2022. This study uses secondary data obtained from the financial statements of infrastructure companies listed on the IDX between 2019 and 2022, which were accessed through the website www.idx.co.id.  The research population consists of 23 infrastructure companies listed on the IDX during the 2019-2022 period. Purposive sampling was used to select a sample of 81 observations, which were analyzed using multiple linear regression. The results show that NPM has an effect on stock prices, while ROI and ROE do not have an impact on stock prices.

This research aims to analyze the best-selling products at Toko Hartati using the K-Means Clustering method. K-Means Clustering is an unsupervised learning algorithm that is effective in grouping data based on certain similar characteristics. In this context, the data used includes the number of sales, product prices, and product categories. Through this analysis, it is hoped that insight can be gained regarding products that have the best sales performance, as well as sales patterns that can be used as a reference in stock management and marketing strategies. The data used in this research includes sales transactions during a certain period, with the aim of identifying product clusters based on sales patterns. The analysis results show the existence of two main product groups, where the first cluster contains products with high sales numbers, which can be classified as best-selling products, while the second cluster includes products with lower sales. These findings provide valuable information for the management of Toko Hartati in determining more targeted marketing strategies and more efficient stock management. This research suggests using the K-Means Clustering method in data-based decision making to improve sales performance in retail stores.