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Penelitian ini bertujuan untuk menganalisis pengaruh Return On Assets (ROA), Current Ratio (CR), dan Debt to Equity Ratio (DER) terhadap harga saham pada PT Multi Indocitra Tbk periode 2007–2025. Metode penelitian yang digunakan adalah kuantitatif dengan data sekunder dari laporan tahunan (Annual Report) perusahaan. Teknik analisis data menggunakan regresi linear berganda dengan bantuan software IBM SPSS Statistics melalui uji asumsi klasik, uji t, uji F, serta analisis koefisien determinasi. Hasil uji parsial menunjukkan bahwa Current Ratio (CR) berpengaruh signifikan terhadap harga saham nilai signifikansi 0,000. Sebaliknya, Return On Assets (ROA) dengan signifikansi 0,558 dan Debt to Equity Ratio (DER) dengan signifikansi 0,148 tidak memiliki pengaruh signifikan. Secara simultan, ketiga variabel independen tersebut berpengaruh signifikan terhadap harga saham nilai signifikansi 0,001. Nilai koefisien determinasi (R2) sebesar 0,637 menandakan 63,7% variasi harga saham dapat dijelaskan oleh ROA, CR, dan DER, sedangkan 36,3% sisanya dipengaruhi variabel lain. Kesimpulannya, hanya CR yang berpengaruh signifikan secara parsial, tetapi seluruh variabel berpengaruh bersama terhadap harga saham.

This study aims to analyze the influence of fundamental and technical factors on stock price movements in the Indonesian capital market. The method used is a literature review with a qualitative descriptive approach, utilizing secondary data obtained from various scientific literature sources as well as stock price data from the Investing platform. The results indicate that there are significant variations in stock prices among companies, reflecting differences in fundamental performance such as profitability, capital structure, and company prospects. In addition, from a technical perspective, stock price movements exhibit dynamic fluctuations, including both increases and decreases, influenced by market sentiment and investor responses to available information. The varying levels of stock volatility also indicate differences in investment risk. Trading volume plays an important role as a key indicator in technical analysis, where high volume reflects strong liquidity and investor interest, while low volume indicates limited market activity. Overall, the findings suggest that fundamental and technical factors have a complementary influence in determining stock price movements. Therefore, investors are advised to integrate both approaches in making investment decisions in order to achieve optimal returns while minimizing risk. This study is expected to contribute to the development of capital market research and serve as a reference for investors and academics.

The stock market is a place to buy shares for profit. In Indonesia, energy stocks are highly unpredictable because global commodity prices change constantly. This study examines what affected energy stock returns in 2024, focusing on trading volume, price swings, company profits, and cash flow. Using financial reports and statistical analysis, all these factors were tested together and individually. The results show that combined, all these factors do affect stock returns. However, when looked at one by one, only the company's net profit truly matters to investors. On the other hand, busy trading, daily price swings, and cash flow have no impact at all. In fact, all the factors studied only account for 14% of stock return movements, while the remaining 86% is driven by other outside forces. In conclusion, for those looking to invest in energy stocks, the most important thing to watch is the company's ability to generate net profit, rather than just looking at how busy daily transactions are in the market.

Penelitian ini bertujuan untuk menganalisis pengaruh inflasi, suku bunga Federal Funds Rate (The Fed), dan pertumbuhan ekonomi Indonesia terhadap Indeks Harga Saham Gabungan (IHSG) selama periode 2005–2025. Penelitian menggunakan pendekatan kuantitatif dengan memanfaatkan data sekunder berbentuk deret waktu (time series) tahunan. Analisis dilakukan menggunakan metode regresi linear berganda dengan bantuan perangkat lunak IBM SPSS Statistics. Sebelum dilakukan estimasi model, terlebih dahulu dilakukan pengujian asumsi klasik yang meliputi uji normalitas, multikolinearitas, autokorelasi, dan heteroskedastisitas untuk memastikan bahwa model regresi memenuhi persyaratan statistik. Pengujian hipotesis dilakukan melalui uji F untuk menguji pengaruh variabel independen secara simultan, uji t untuk menganalisis pengaruh masing-masing variabel secara parsial, serta koefisien determinasi (R²) untuk mengukur kemampuan model dalam menjelaskan variasi IHSG. Hasil penelitian menunjukkan bahwa model regresi telah memenuhi seluruh asumsi klasik sehingga layak digunakan dalam analisis. Pengujian simultan membuktikan bahwa inflasi, suku bunga The Fed, dan pertumbuhan ekonomi secara bersama-sama berpengaruh signifikan terhadap IHSG. Sementara itu, hasil uji parsial menunjukkan bahwa hanya suku bunga The Fed yang berpengaruh negatif dan signifikan terhadap IHSG, sedangkan inflasi dan pertumbuhan ekonomi tidak menunjukkan pengaruh yang signifikan secara statistik. Nilai koefisien determinasi sebesar 52,4% mengindikasikan bahwa variasi IHSG dapat dijelaskan oleh ketiga variabel independen dalam model, sedangkan 47,6% sisanya dipengaruhi oleh faktor lain di luar penelitian. Temuan ini diharapkan dapat menjadi referensi bagi investor maupun pembuat kebijakan dalam memahami pengaruh kondisi makroekonomi terhadap dinamika pasar modal Indonesia.

Bank stock price prediction is an important topic in the application of information technology because stock price movements are dynamic, sequential, and influenced by historical market patterns. This study aims to predict Indonesian banking stock prices using the Long Short-Term Memory method and evaluate the effect of Bayesian Optimization on model performance. The data used in this study consists of daily historical stock data of BBCA, BBNI, BBRI, BBTN, and BMRI from May 4, 2020, to May 4, 2026, obtained from Yahoo Finance. The input features include opening price, highest price, lowest price, closing price, and trading volume, while the prediction target is the stock closing price. The results show that the baseline model produced MAPE values ranging from 1.892% to 3.147%. The best baseline performance was obtained on BBCA with an R² value of 0.933, followed by BBTN with an R² value of 0.902. After optimization, performance improvement occurred on BBTN, with MAPE decreasing from 3.147% to 2.482% and R² increasing from 0.902 to 0.935. For BMRI, MAPE decreased from 2.385% to 2.206%, and R² increased from 0.687 to 0.743. This study concludes that Long Short-Term Memory can be used to predict Indonesian banking stock prices, while Bayesian Optimization can selectively improve model performance depending on the characteristics of each stock dataset.

Penelitian ini bertujuan untuk mengetahui pengaruh Debt to Equity Ratio (DER), Total Assets Turnover (TATO) dan Return on Assets (ROA) terhadap Price to Book Value (PBV) pada perusahaan Subsektor Otomotif dan Komponen yang terdaftar di Bursa Efek Indonesia (BEI) periode 2021-2024. DER rasio keuangan yang menunjukkan perbandingan antara jumlah utang (liabilitas) perusahaan dan modal sendiri (ekuitas) TATO mencerminkan tingkat efisiensi bagaimana perusahaan menggunakan keseluruhan aset dalam menciptakan kapasitas penjualan. ROA rasio yang digunakan untuk mengukur seberapa efektif perusahaan menghasilkan laba bersih dari total asetnya. PBV rasio yang digunakan untuk mengukur tingkat harga saham apakah overvalued atau undervalued. Penelitian ini menggunakan data sekunder berupa laporan keuangan tahunan pada 10 perusahaan Subsektor Otomotif dan Komponen yang terdaftar di Bursa Efek Indonesia periode tahun 2021-2024 yang dipublikasikan melalui situs www.idx.co.id dan website pada masing-masing perusahaan. Metode penentuan sampel yang digunakan Purposive Sampling dengan memperoleh sampel 10 perusahaan subsektor otomotif dan komponen. Teknik analisis data yang digunakan dalam penelitian ini adalah analisis deskriptif dan analisis verifikatif dengan menggunakan analisis model regresi data panel, uji asumsi klasik, uji koefisien determinasi, uji hipotesis dengan menggunakan uji parsial (uji t) dan uji simultan (uji f). Dalam menganalisis data penelitian ini menggunakan aplikasi program alat bantu analisis statistika Eviews versi 12. Berdasarkan hasil penelitian diperoleh bahawa DER dan TATO secara parsial tidak berpengaruh terhadap PBV. ROA secara parsial berpengaruh positif dan signifikan terhadap PBV. Secara simultan DER, TATO dan ROA tidak berpengaruh terhadap PBV pada perusahaan Subsektor Otomotif dan Komponen yang terdaftar di Bursa Efek Indonesia periode 2021-2024.

Stock price volatility in the technology sector has become an important concern for investors due to the sector’s high uncertainty, rapid business transformation, and sensitivity to economic changes. Understanding the financial factors that influence stock price fluctuations is therefore essential for improving investment decision-making and risk assessment. This research investigates the influence of financial performance, leverage, and earning volatility on the stock price volatility of technology companies listed on the Indonesia Stock Exchange during the 2022–2024 period. A quantitative causal approach was employed using secondary data obtained from annual financial statements and stock market data. The sample consisted of 23 technology companies selected through purposive sampling, resulting in 69 observations. Multiple linear regression analysis was applied after fulfilling the classical assumption tests. The findings indicate that financial performance, proxied by Return on Assets (ROA), has a negative but insignificant relationship with stock price volatility, while leverage, measured by Debt to Equity Ratio (DER), shows a positive but insignificant effect. In contrast, earning volatility demonstrates a positive and statistically significant influence on stock price volatility. Simultaneously, the three independent variables significantly affect stock price volatility, although the explanatory power of the model remains relatively limited. These findings provide additional empirical evidence regarding signaling theory in the context of emerging capital markets and highlight earning volatility as a key consideration for investors when evaluating technology-sector stocks characterized by high uncertainty and dynamic business environments.

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 examine the differences in stock prices before and after the Palestine-Israel ceasefire event in fast-food restaurant companies,  Pizza Hut and KFC. International-scale events may influence investor perceptions, as reflected in stock price movements in the capital market. This study employs a comparative quantitative approach using stock price data collected over 30 days before and 30 days after the ceasefire event. The analyzed data consist of secondary data processed through descriptive statistics, normality tests, and hypothesis testing. The findings indicate that the average stock price of PZZA increased after the event, whereas FAST experienced a decline in its average stock price. These results reveal differences in stock prices between the periods before and after the ceasefire event in both companies. The findings further suggest that geopolitical events are associated with changes in stock prices in the fast-food restaurant industry, although market responses differ across companies. Therefore, future studies are recommended to expand the scope of research objects and extend the observation period to obtain a more comprehensive understanding of market responses to international events.

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 prices of banking companies are often associated with financial performance indicators that reflect a company’s ability to generate profits, maintain capital adequacy, and manage credit risk. This study aims to analyze the effect of Return on Assets (ROA), Capital Adequacy Ratio (CAR), and Non-Performing Loan (NPL) on stock prices of banking companies listed on the Indonesia Stock Exchange during the 2020–2024 period. This research employs a quantitative approach using multiple linear regression analysis. The sample was determined through purposive sampling, resulting in 50 observations, using secondary data obtained from companies’ financial statements.The results indicate that ROA has a positive and significant effect on stock prices, CAR has a negative and significant effect, and NPL has a positive and significant effect on stock prices. These findings suggest that profitability and credit risk are important considerations for investors, while a high level of capital adequacy is not necessarily positively responded to by the market.

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.

The purpose of this research is to determine the effect of microeconomics on stock prices at PT. Industri Jamu dan Farmasi Sido Muncul Tbk. during the period 2014 to 2023. The method used in this study is a descriptive quantitative approach using secondary data in the form of company financial reports. The samples analyzed is the financial report of PT. Industri Jamu dan Farmasi Sido Muncul Tbk. 2014 - 2023. Data analysis was performed using SPSS software version 30. The analysis techniques used include descriptive analysis tests, classical assumption tests, multiple linear regression, and hypothesis tests. The results of this study indicate that the Earnings Per Share variable has a significant partial effect on stock prices (T value 7.383 > T table 2.365 and a significance value of 0.001 <0.05), and the Price to Book Value variable also has a significant effect on stock prices (T value 23.748 > T table 2.365 and a significance value of 0.001 <0.05). Simultaneously, the variables Earnings Per Share and Price to Book Value have a significant effect on stock prices with a calculated F value of 331.779 > F table 4.737 and a significance value of 0.001 < 0.05.

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.

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 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.

Studi ini berfokus pada perusahaan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) antara tahun 2020 hingga 2023 dan mengkaji bagaimana harga saham dipengaruhi oleh Earnings Per Share  (EPS) sebagai pemoderasi dan rasio keuangan sebagai variabel independennya. Ada dua rasio keuangan yang diteliti yaitu Capital Adequacy Ratio (CAR) dan Return on Assets (ROA). Penelitian ini menggunakan pendekatan Ordinary Least Squares (OLS). Hasil penelitian menunjukkan bahwa ROA berpengaruh terhadap harga saham, sedangkan CAR tidak berpengaruh. Selain itu, telah terbukti bahwa EPS memoderasi hubungan antara return on assets (ROA) dan harga saham. Diharapkan hasil penelitian ini akan berguna sebagai referensi untuk studi mendatang dan mendorong penelitian terkait topik yang sama.

The purpose of this research is to analyze the influence of Earning Per Share and Return On Assets on Stock Price at PT Surya Citra Media Tbk in 2014-2023. This Research is a type of quantitative research using descriptive analysis methods and using data on financial statements in the form of balance sheets and income statement PT Surya Citra Media Tbk. Based on the results of the study showed that patially Earning Per Share and Return On Asset had a significant effect on the stock price in PT Surya Citra Media Tbk. in 2014-2023. Then simultaneously it is known that Earning Per Share and Return On Assets have a significant effect on stock price in PT Surya Citra Media Tbk. in 2014-2023.