Publication Search

Investment decisions in pharmaceutical manufacturing companies listed on the Indonesia Stock Exchange (IDX) are influenced by fundamental analysis and stock price fluctuations. Stock prices reflect market perceptions shaped by profitability, liquidity, and capital structure. This study examines the effects of Return on Assets (ROA), Current Ratio (CR), and Debt-to-Equity Ratio (DER) on stock prices, both partially and simultaneously. Using a quantitative approach, the study analyzes secondary data from audited financial statements and stock prices of 12 pharmaceutical companies during 2022–2024, totaling 36 observations. Panel data regression with EViews 12 is applied. Results show that ROA and DER have positive and significant effects on stock prices, while CR has a negative but insignificant effect. Simultaneously, all three variables significantly influence stock prices, with an adjusted R² of 73%, indicating strong explanatory power. Profitability (ROA) is the most influential factor, followed by capital structure (DER), while liquidity (CR) shows no significant impact.

The Indonesian capital market has become a vital pillar of the national economy, providing opportunities for companies to obtain funding while simultaneously providing an investment vehicle for the wider community. In this context, stocks are the most sought-after instrument due to the potential returns they offer. However, stock investment is constantly faced with uncertainty, with fluctuating stock prices often presenting challenges for investors, especially those without a thorough understanding of the company's fundamental performance. An interesting phenomenon, the starting point of this research, is the quite extreme price movements of BIPI shares over the past decade. From 2015 to 2021, BIPI's share price remained stagnant at Rp 50 per share, a condition often referred to by market participants as "gocap" (goat capit). This condition reflects low investor interest in the company's shares, possibly due to high risk perceptions or unconvincing fundamental performance.

This study aims to analyze the effect of inflation and interest rates on the stock prices of banking companies listed in the IDX80 index on the Indonesia Stock Exchange for the 2019–2024 period. Research data were obtained from official reports of banking company stock prices as well as inflation and interest rate data from Bank Indonesia. The study used a quantitative approach with multiple linear regression methods through the SPSS application, and classical assumption tests were conducted as a requirement for analysis. The study population included all IDX80 banking companies, with a saturated sampling technique resulting in five banks that met the criteria during the study period. The results of the partial test indicate that inflation has a positive and significant effect on stock prices, while interest rates have a negative and significant effect on stock prices. This indicates that stable inflation can still improve the performance of the banking sector, while rising interest rates tend to depress stock prices due to increased borrowing costs and a shift in investment to other instruments. The results of the simultaneous test also show that inflation and interest rates together have a significant effect on the stock prices of IDX80 banking companies. The results show that inflation has a significant positive effect on stock prices with a significance value of 0.034, while interest rates have a significant negative effect with a significance value of 0.018. Simultaneously, inflation and interest rates have a significant effect on stock prices with a calculated F value of 14.549 > Ftable 2.70 and a significance of 0.000 < 0.05.

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.

The dynamic fluctuations in stock prices present a major challenge for investors in making informed decisions. To anticipate such uncertainties, forecasting methods that can provide accurate predictions are required. This study compares two time series forecasting methods Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (Holt) in predicting the stock prices of PT Telkom Indonesia (TLKM). The dataset consists of monthly closing prices from January 2018 to December 2023. The performance of each model is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results show that the ARIMA(1,1,1) model yields higher predictive accuracy than the Holt method, with MAE of 787.71, MSE of 771,844.2, and RMSE of 878.55. In contrast, the Holt method records a MAE of 837.19, MSE of 878,393.4, and RMSE of 937.23. These findings confirm that ARIMA is superior in capturing the complex patterns of stock price movements and is more effective in volatile market conditions such as the stock exchange.

This study aims to analyze the reaction of the Indonesian capital market to the announcement of Donald Trump’s import tariff policy using an event study approach. Market reactions are measured through abnormal return and trading volume activity of exporting companies listed on the Indonesia Stock Exchange (IDX), with an event window of three trading days before and three trading days after the initial tariff announcement on April 2, 2025 and the revised tariff announcement on July 15, 2025. This study employs secondary data in the form of daily stock prices and trading volumes, analyzed using descriptive statistics, normality tests, and the Wilcoxon Signed Rank Test. The results indicate that the Indonesian capital market reacts to the announcement of Donald Trump’s import tariff policy, as reflected by differences in abnormal return and trading volume activity before and after the announcements, thereby supporting signaling theory and the semi-strong form of market efficiency.

Perkembangan kecerdasan buatan (AI) mendorong inovasi dalam analisis keuangan, termasuk prediksi harga saham yang fluktuatif. Penelitian ini bertujuan memprediksi harga saham PT Garudafood Putra Putri Jaya Tbk menggunakan model ARIMA dengan penanganan Outlier sebagai pendekatan awal menuju sistem prediksi yang lebih adaptif. Data harga penutupan harian dari Yahoo Finance dianalisis melalui uji stasioneritas, identifikasi model ARIMA, deteksi Outlier berbasis log-return, serta evaluasi performa menggunakan RMSE, MAE, dan MAPE. Hasil penelitian menunjukkan bahwa ARIMA Outlier memberikan performa lebih baik dibandingkan ARIMA dasar. ARIMA standar menghasilkan MAPE 1.32% dan AIC –899.46, sedangkan ARIMA dengan tiga dummy Outlier mencapai MAPE 1.16% dan AIC –900.37. Peramalan 14 hari ke depan menunjukkan pola yang stabil pada kisaran Rp 370–371. Pada data uji, ARIMA dasar memberikan akurasi terbaik pada pertengahan Agustus, sedangkan ARIMA Outlier mencapai akurasi tertinggi pada akhir Agustus dengan prediksi Rp 370.2 yang sangat dekat dengan harga aktual Rp 370.4. Hasil ini menunjukkan bahwa penanganan Outlier meningkatkan ketepatan model, sehingga ARIMA Outlier dapat digunakan sebagai fondasi awal menuju pengembangan sistem prediksi keuangan berbasis AI.

In the investment world, stock returns are the leading indicator of a company’s performance and the basis for investor decision-making in the capital market. Fluctuations in stock returns reflect market expectations of the company’s prospects. The retail sector in Indonesia is facing significant pressure from post-pandemic shifts in consumer behavior and increased competition. This study aims to analyze the effect of financial distress, company size, liquidity, operating cash flow, and accounting profit on stock returns in retail sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the period 2021 to 2023. This type of research is causally associated with a quantitative approach. The data used is secondary, in the form of financial statements from retail companies. The sampling technique used was purposive, yielding a total of 39 data points from 13 retail companies. Data testing was carried out using SPSS version 24. The results showed that partially, the variables of financial distress, company size, liquidity, and accounting profit had no significant effect on stock returns. Meanwhile, operating cash flow positively impacts stock returns. These findings indicate that fundamental indicators are not always the main determinants of stock returns. Therefore, investors are advised also to consider external factors such as market sentiment, macroeconomic conditions, and government policies that may have a greater influence on stock performance in the capital market.

This study aims to examine the effect of profitability ratios, namely Earnings per Share (EPS), Net Profit Margin (NPM), Return on Assets (ROA), and Return on Equity (ROE), on the stock price of PT Ciputra Development Tbk during the 2016–2023 period. The research employs a quantitative approach with a causal research design using secondary data derived from quarterly financial statements and stock closing prices published by the Indonesia Stock Exchange. The data were analyzed using multiple linear regression, supported by classical assumption tests, partial hypothesis testing (t-test), simultaneous testing (F-test), and the coefficient of determination (R²). The results show that EPS, NPM, and ROA do not have a significant effect on stock prices, while ROE has a positive and significant effect. Simultaneously, all profitability variables do not significantly influence stock prices. The coefficient of determination indicates that profitability ratios explain a relatively small proportion of stock price variation, suggesting that stock prices in the property sector are influenced more by external and market-related factors than by short-term profitability indicators. These findings imply that ROE is the most relevant profitability indicator for investors in assessing property sector stocks, while other profitability ratios play a limited role.

This study aims to estimate changes in the Indonesian Sharia Stock Index (ISSI) from 2020 to 2025 using the Autoregressive Integrated Moving Average (ARIMA) model. The growth of the Islamic stock market in Indonesia has increased rapidly, driven by public awareness of investments that follow sharia principles, as well as changes in macro and microeconomic conditions, especially during the COVID-19 pandemic which has had a significant impact on the financial market. This study relies on monthly ISSI data taken from official sources and analyzed with a quantitative approach using the time series method using EViews version 13 software. Statistical analysis and stationarity tests indicate that the ISSI data exhibits an increasing trend pattern and quite high volatility, so that a differentiation process is necessary to achieve stationarity. Based on the results of model testing and the selection of optimal information criteria, the ARIMA (1,1,1) model was selected as the most appropriate to capture the autocorrelation pattern and produce accurate short-term predictions. Projections indicate a stable growth trend until the end of 2025, with an estimated index of more than 8.3 million. The findings of this study indicate that the ARIMA model is an effective tool for forecasting ISSI movements and can be a strategic consideration for investors, financial institutions, and policymakers in developing sustainable investment strategies in the Indonesian Islamic stock market.

This study aims to analyze the capital market reaction to the groundbreaking event of the new capital city (IKN) on the stock prices of property and construction sector companies listed on the Indonesia Stock Exchange (IDX). This research employs a quantitative approach using the event study method with an observation period of 11 days, consisting of 5 days before (t-5), the event day (t), and 5 days after (t+5) the event. The sample includes property and construction sector companies that were actively traded during the observation period. Data analysis was conducted using the Paired Sample t-test through SPSS to examine differences in Abnormal Return (AR), Cumulative Abnormal Return (CAR), and Trading Volume Activity (TVA) before and after the event. The results show that there is no significant difference in AR and TVA, but there is a significant difference in CAR, indicating that the market reacted cumulatively to the groundbreaking IKN information. These findings support the semi-strong form of market efficiency theory, suggesting that the market requires time to fully reflect information into stock prices.

This study aims to see the effect of Debt to Equity Ratio (DER) and Return on Assets (ROA) on Stock Price in PT. Wilmar Cahaya Indonesia, Tbk which is listed on the IDX during the period 2015–2022. The data used in this study is in the form of the company's annual financial statements obtained through secondary sources. This study uses a quantitative approach with multiple linear regression analysis methods, while data processing is carried out using the SPSS application. The results of the study show that partially the Debt to Equity Ratio (DER) variable has a negative effect on the Share Price, while the Return on Assets (ROA) does not have a positive effect on the company's Share Price. However, the results of the simultaneous test show that DER and ROA together have a positive and significant influence on the Stock Price. These findings provide an idea that the combination of capital structure and profitability remains an important indicator in assessing the performance of a company's shares even though their partial relationships show different tendencies. In addition, this research can be a reference for investors in considering the company's fundamental condition before making investment decisions, as well as provide additional insights for management in managing the capital structure more optimally.

This study aims to analyze the Effect of Return on Equity (ROE), Total Asset Turnover (TATO), Net Profit Margin (NPM) on Stock Prices in food and beverage companies listed on the Indonesia Stock Exchange for the 2020-2024 period. The approach in this study is to use a quantitative approach, and based on the objectives, this type of research is causal. The independent variables in this study include Return on Equity (ROE), Total Asset Turnover (TATO), and Net Profit Margin (NPM) and the dependent variable in this study is Stock Price. The population in this study is food and beverage companies listed on the Indonesia Stock Exchange, totaling 27 companies for the 2020-2024 period. This study uses the Purposive Sampling method, selecting 18 companies multiplied by 5 periods, resulting in a sample size of 90 samples in this study. This study uses descriptive statistical analysis using secondary data with descriptive statistical tests. Continued with the classical assumption test using the multiple regression model hypothesis testing method. This study uses panel data regression tool analysis with the help of SPSS 26 application tools. The results of the study show that: (a) Return on equity (ROE) has a positive effect on share prices, (b) Total Asset Turnover (TATO) does not have an effect on share prices, (c) Net Profit Margin (NPM) has a positive effect on share prices.

The purpose of this research is to analyze and find out how the company's growth, capital structure and company size affect stock prices in sub-sector, ceramics, porcelain and glass companies listed on the IDX for the 2018-2023 period. This research is an associative quantitative research using secondary data taken from the company's annual financial statements. The sampling technique in this study uses purposive sampling. In this study, 48 samples were obtained for 6 years (20182023). The analysis tool used in the regression analysis of panel data was conducted using E-views 13. Based on the research that has been carried out, it can be concluded that the company's growth partially has a significant effect on the stock price, the company's capital structure and size partially do not have a significant effect on the stock price. Then  the company's growth, capital structure and company size simultaneously have a significant effect on the stock price of companies in the ceramics, porcelain and glass sub-sector listed on the IDX for the 2018-2023 period.

This study aims to analyze the effect of cum and ex-dividend dates and company size on stock prices using the Dividend Payout Ratio (DPR) as a moderating variable. This study uses multiple linear regression analysis with moderating variables on companies listed on the Indonesia Stock Exchange. This research is based on signaling theory, which states that dividend information can serve as a signal for investors in making investment decisions. The results of the study indicate that all independent and moderating variables in the model simultaneously have a significant influence on stock prices. This suggests that the regression model used in this study is valid and can comprehensively explain stock price variations. This study implies that companies need to develop a more structured financial communication strategy, particularly in the disclosure of dividend information. Not only should the timing of dividend distribution be communicated, but the number of dividends to be distributed should also be clearly communicated to strengthen investor response. The implementation of this strategy must be accompanied by compliance with OJK and IDX regulations to maintain market confidence and increase the value of company shares.

This study aims to analyze the effect of Total Asset Turnover (TATO) on stock prices at PT Baramulti Suksessarana Tbk during the 2014–2023 period. TATO is an activity ratio that measures how efficiently a company utilizes its total assets to generate sales. This research employs a quantitative associative approach using secondary data obtained from the company’s annual financial statements published by the Indonesia Stock Exchange. Data were analyzed using simple linear regression to determine the relationship between the independent variable (TATO) and the dependent variable (stock price). The results show that TATO has a positive and significant effect on stock prices, with a correlation coefficient of 0.859 and a significance value of 0.001 (p < 0.05). This indicates that the more efficiently a company uses its assets to generate sales, the higher its stock price will be. The findings support the signaling theory and efficient market hypothesis, suggesting that asset efficiency serves as a positive signal for investors in evaluating firm performance.

This study aims to analyze the effect of changes in interest rates, exchange rates, economic growth, and world oil prices on stock returns in the transportation and logistics sector in Indonesia during the period 2006–2024. This sector was chosen because it is highly vulnerable to fluctuations in macroeconomic factors that have a direct impact on companies' operating costs and financial performance. The method used is multiple linear regression with an annual panel data approach, using a sample of transportation and logistics companies listed on the Indonesia Stock Exchange. The independent variables include changes in interest rates, exchange rates, economic growth, and oil prices, while the dependent variable is stock returns. The results show that, partially, only changes in interest rates have a significant negative effect on stock returns. Conversely, exchange rates, economic growth, and oil prices have no statistically significant effect. Simultaneously, these four variables also show no significant effect on stock returns. This study makes a new contribution through the use of a long observation period and a focus on the transportation and logistics sector, thereby providing a deeper understanding of this sector's sensitivity to macroeconomic conditions.

The capital market is a place for various investment instruments, ranging from short-term to long-term. Before buying shares in the capital market, investors need to analyze the share prices of selected companies to predict large profits. The higher the share price, the greater the possibility of making a profit. This study aims to determine the factors that influence the stock prices of companies in the hotel, resort, and shipping sub-sectors listed on the IDX for the period 2019–2024. The dependent variable in this study is stock price, while the independent variables are financial performance and sustainability report disclosure. Financial performance variables are proxied by DER, Current Ratio, ROA, and TATO. This is a quantitative study using secondary data obtained from annual reports and sustainability reports taken from the companies' official websites. The number of samples used in this study is 10 companies using classical assumption techniques, multiple linear regression analysis, determination tests, and ending with hypothesis testing. The results show that DER and Current Ratio have a negative effect on stock prices. ROA, TATO, and sustainability report disclosure partially have no effect on stock prices. Meanwhile, financial performance and sustainability report disclosure simultaneously affect stock prices.

This study aims to analyze the effect of financial ratios, specifically the Current Ratio (CR) and Return on Assets (ROA), on stock returns of food and beverage subsector companies listed on the Indonesia Stock Exchange (BEI) during the period 2022–2024. The approach used is quantitative with a descriptive method and multiple linear regression analysis, along with classical assumption tests to ensure data validity. The sample consists of 18 companies that meet the purposive sampling criteria based on the availability of complete financial statements, observation periods, and no losses. Data were obtained from annual financial reports available on the official BEI website and individual companies. The analysis results show that, simultaneously, both Current Ratio and Return on Assets have a positive and significant effect on stock returns, indicating that liquidity and profitability are important factors affecting investment returns in this sector. Partially, ROA has a significant positive effect on stock returns, while the effect of CR is positive but not significant. These findings provide strategic implications for companies in managing financial aspects and for investors in making investment decisions based on financial indicators. This study is expected to contribute to the development of knowledge in corporate finance.

This study aims to examine the effect of Environmental, Social, and Governance (ESG) disclosure and energy price volatility on stock returns of energy sector companies listed on the Indonesia Stock Exchange (IDX) during the 2022–2024 period. A quantitative approach was employed using multiple linear regression as the analytical method. The sample consisted of 10 energy companies selected through purposive sampling, based on the availability of sustainability reports, stock price data, and research completeness. The results indicate that ESG disclosure has a positive and significant effect on stock returns, suggesting that companies with higher sustainability transparency tend to gain stronger investor confidence. Energy price volatility also shows a positive and significant effect on stock returns, reflecting the sector’s sensitivity to global energy price dynamics. Simultaneously, both variables significantly influence stock returns, although the relatively low coefficient of determination implies that other factors should also be considered. This study highlights the importance of integrating internal factors (ESG) and external factors (energy price volatility) for investors when making investment decisions in the energy sector.