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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.

Perseroan Terbatas (PT) merupakan pilar utama hukum ekonomi Indonesia yang diatur dalam Undang-Undang Nomor 40 Tahun 2007 tentang Perseroan Terbatas (UUPT). Rapat Umum Pemegang Saham (RUPS) sebagai organ tertinggi perseroan memiliki kewenangan eksklusif yang pelaksanaannya dibebankan kepada Direksi. Permasalahan yang dikaji meliputi: (1) akibat hukum dari pelaksanaan RUPS yang tidak sah; (2) analisis atas pelaksanaan RUPS yang tidak sah berdasarkan Putusan Mahkamah Agung Nomor 773 PK/Pdt/2019; dan (3) tanggung jawab Direksi atas pelaksanaan RUPS yang tidak sah. Penelitian ini menggunakan metode yuridis normatif dengan sumber data sekunder berupa bahan hukum primer, sekunder, dan tersier. Hasil penelitian menunjukkan bahwa: (1) pelaksanaan RUPS yang tidak sah menimbulkan akibat hukum pada status keputusan, akta notaris, dan perbuatan hukum turunan, di mana cacat materiil mengakibatkan batal demi hukum, sedangkan cacat formil dapat dibatalkan melalui pengadilan; (2) analisis Putusan MA No. 773 PK/Pdt/2019 menunjukkan adanya ketidakpastian hukum akibat perbedaan penafsiran, menegaskan bahwa substansi lebih penting daripada formalitas, serta menjamin perlindungan hukum bagi pemegang saham yang dirugikan; dan (3) Direksi bertanggung jawab secara pribadi atas RUPS yang tidak sah dan tidak dapat berlindung pada badan hukum perseroan, serta tidak dapat menggunakan prinsip business judgment rule apabila terbukti melakukan pelanggaran hukum.

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.

This study aims to analyze the comparison of financial distress levels measured using the Current Ratio (CR) and the Altman Z-Score model and their relationship with stock returns in PT Charoen Pokphand Indonesia Tbk and PT Japfa Comfeed Indonesia Tbk during the period 2020–2025. The research method used is a quantitative approach with a comparative design, and the sampling technique applied is purposive sampling. Data analysis was conducted using descriptive statistics and multiple linear regression.The results indicate that there is no statistically significant difference between the two companies in terms of hal Likuidity (Current Ratio) dan Financial Distress (Altman Z-Score). Descriptively, CPIN has an average Current Ratio of 1.959 and a Z-Score of 3.700, while JPFA shows slightly lower values but remains within the safe zone. Furthermore, regression results reveal that liquidity and financial distress do not have a significant effect on stock returns. Both companies are classified in the safe zone, indicating a healthy financial condition and low risk of financial distress, while stock returns tend to be volatile and influenced by external factors.The study recommends that companies maintain a balance between liquidity, profitability, and capital structure to sustain financial stability. Investors are advised to consider not only financial ratios but also external factors in decision-making. Future researchers are encouraged to expand the sample size and include additional variables to obtain more comprehensive results.

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.

Stock market volatility represents a key indicator of financial market uncertainty, particularly in emerging economies where market structures are still evolving and are highly sensitive to global shocks. This study aims to analyze and compare the volatility dynamics of stock markets in four Asian emerging economies: Indonesia, India, Malaysia, and Thailand. The research employs a quantitative approach using daily stock index data from January 2011 to January 2026 obtained from Yahoo Finance. Stock returns are calculated using logarithmic transformation and analyzed using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model. Prior to model estimation, stationarity and ARCH effect tests are conducted to ensure the validity of volatility modeling. The empirical findings indicate that all return series exhibit non-normal distribution, strong volatility clustering, and significant ARCH effects. The estimation results show that both ARCH and GARCH parameters are statistically significant, with persistence levels close to unity across all markets, implying that volatility shocks tend to persist over a long period. These findings suggest that emerging stock markets in Asia are highly sensitive to external shocks and exhibit long-memory volatility behavior. The results provide important implications for investors and policymakers in designing effective risk management and market stabilization strategies.

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 was conducted to evaluate the influence of Total Asset Turnover (TATO), Debt to Equity Ratio (DER), and Net Profit Margin (NPM) in predicting stock return fluctuations. The study focuses on retail sector issuers listed on the Indonesian Stock Exchange (IDX) between 2021 and 2024. Through the application of panel data regression analysis, the study determined that the Common Effects Model (CEM) is the most appropriate estimation method. This decision was made based on a series of tests including the Chow Test and the Lagrange Multiplier. Although classical assumption testing showed symptoms of heteroscedasticity, this problem was addressed using the EGLS (cross-sector weighting) Panel method to ensure the validity of the estimates. Based on partial testing, it is found that TATO and NPM variables have a positive and significant contribution to stock returns, while DER is found to have no significant effect. Collectively, all independent variables had a significant effect, with the Adjusted R-Square value reaching 27.80%. This indicates that for investors in the retail sector, profitability and operational efficiency are important indicators in making investment decisions.

Shares trading below their intrinsic value present compelling return opportunities, particularly for long‑term investors. This study aims to assess the valuation of eight food‑and‑beverage issuers listed on the Indonesia Stock Exchange (IDX) over the 2021–2025 period using two market‑based valuation instruments: the Price to Earnings Ratio (PER) and the Price to Book Value (PBV). A quantitative descriptive design was employed, and a purposive sampling technique selected eight issuers: INDF, ICBP, MYOR, ROTI, GOOD, CLEO, CMRY, and CAMP. The sectoral benchmarks obtained were an average industry PER of 22.64 times and an average industry PBV of 3.45 times. Comparative analysis reveals that INDF (PER 7.38x; PBV 0.59x), ICBP (PER 17.60x; PBV 1.83x), ROTI (PER 18.86x; PBV 2.47x), and CAMP (PER 16.59x; PBV 1.78x) are undervalued relative to the industry average and therefore merit consideration as buy candidates, while MYOR, GOOD, CLEO, and CMRY are overvalued. INDF emerges as the most attractive investment candidate because its PBV remained consistently below 1.00 throughout the observation window, a condition recognized in value‑investing literature as deeply undervalued. The findings reinforce the argument that combining PER and PBV serves as a reliable tool for identifying high‑potential stocks from a fundamental analysis perspective.

This study aims to examine the effect of Return on Assets (ROA), Debt to Equity Ratio (DER), and e-IPO regulation on the level of IPO underpricing on the Indonesia Stock Exchange during the 2021–2025 period. The research employs a causal quantitative approach using multiple linear regression analysis. Secondary data were collected from the prospectuses and financial statements of companies conducting Initial Public Offerings (IPOs).The results indicate that ROA does not have a significant effect on underpricing (significance value = 0.181). Similarly, DER is found to have no significant influence on underpricing (significance value = 0.268). The simultaneous test also shows a non-significant result, with an F-significance value of 0.120, suggesting that the independent variables collectively do not affect IPO underpricing. Furthermore, the coefficient of determination (R²) of 0.175 implies that only 17.5% of the variation in underpricing can be explained by the variables included in the model, while the remaining 82.5% is attributable to other factors outside the study, such as market sentiment, underwriter reputation, and oversubscription levels. These findings suggest that investors in the Indonesian IPO market tend to prioritize short-term capital gain opportunities rather than relying on firms’ financial fundamentals. Consequently, accounting-based indicators are not sufficiently influential in shaping stock prices during the first day of trading.

This study aims to analyze the impact of the USD/CNY exchange rate and the Federal Reserve interest rate on the stock returns of Volkswagen AG. Volkswagen AG is chosen as the object of analysis because it is a multinational corporation with significant exposure to the Chinese market, making it highly sensitive to fluctuations in global economic conditions, particularly exchange rate movements and monetary policy changes. The study adopts a quantitative research approach using multiple linear regression analysis to examine the relationships between variables. The data used are monthly secondary data covering the period from 2017 to 2023, resulting in 84 observations. The dependent variable in this study is Volkswagen AG stock returns, while the independent variables consist of the USD/CNY exchange rate and the Federal Funds Rate. The empirical results show that the USD/CNY exchange rate has a negative and statistically significant effect on Volkswagen AG stock returns, indicating that currency depreciation or appreciation plays a crucial role in influencing investor sentiment and firm valuation. In contrast, the Federal Funds Rate does not show a statistically significant effect on stock returns during the observed period. However, the simultaneous test indicates that both variables jointly have a significant influence on Volkswagen AG stock returns. Overall, the findings suggest that exchange rate risk is more dominant than U.S. monetary policy in affecting the stock performance of Volkswagen AG over the study period.

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.

This paper focuses on a legal review of foreign investment regulations in Indonesia, a crucial aspect that underpins most of the discussion. Furthermore, it frequently highlights the implications of legal regulations on investment, including foreign investment, in several related regulations, such as the Job Creation Law and the Investment Law, for market volatility, corporate governance, and stock prices in Indonesia. This paper emphasizes a normative-empirical context, focusing on a review of capital market investment regulations and secondary analyses conducted through several journals reporting on the effectiveness of foreign investment for local companies, enhancing their image as local companies, a trend inevitably driven by local interests. This is further supported by the use of various important theories, such as foreign investment theory, the legal framework for foreign investment, stock performance theory, and efficient investment, as crucial theoretical considerations in the discussion. The point of the results of the discussion in this writing is then emphasized on its focus, namely the results of the review of the legal regulations regarding capital markets that include foreign capital markets, which also discusses the results of research reports from various journals related to the implications of foreign investment regulations as well as the challenges and discussions of harmonization regarding existing investment regulations in Indonesia.

This study examines thee regulations governing the post-notification obligation for share acquisitions from the perspective of competition law in Indonesia, as well as efforts to optimise it as an effective supervisory instrument. Indonesia adopts a post-notification system as stipulated in Law No. 5 of 1999 and its implementing regulations, which require business entities to report acquisition transactions to the KPPU after the transaction has taken effect. Although this system provides flexibility for business entities, in practice there are a number of weaknesses, including its reactive nature, low levels of compliance, and limitations in the effectiveness of oversight in preventing anti-competitive effects. This study employs a normative legal method using legislative, conceptual, and comparative approaches, as well as an analysis of KPPU decisions. The research findings indicate that the post-notification system is not yet optimal in maintaining healthy business competition. Therefore, there is a need to strengthen oversight mechanisms, improve business compliance, and update legal policies to be more adaptive, including the possibility of limited integration of pre-notification elements. It is hoped that these optimisations will enhance the effectiveness of acquisition control and prevent monopolistic practices and unhealthy business competition in Indonesia.

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.

Employee cooperatives play a strategic role as an economic buffer for teachers and school staff, particularly in providing access to safe, transparent, and equitable financial services. This study aims to evaluate the salary and share deduction system in managing member loans at the “Maju Terus” Employee Cooperative of SMKS Yohanes XXIII Maumere. The evaluation focuses on salary deduction procedures for active members, share deduction mechanisms for inactive members, handling of arrears, system effectiveness, obstacles encountered, causes of obstacles, and improvement efforts that have been made. The research method used is a descriptive qualitative approach with data collection techniques through observation, interviews, and documentation studies. The study results show that the salary and share deduction system has been implemented in a structured and effective manner, successfully maintaining the non-performing loan rate below 2% for the past three years, as well as supporting cash flow stability and increasing cooperative revenue. However, the implementation of this system still faces obstacles such as late payment of salary deductions by the school treasurer, insufficient shares of inactive members to cover arrears, a manual recording system, and minimal outreach to new members. Improvement efforts that have been made include monthly coordination meetings, intensive outreach, transparency through membership books, quarterly reporting, and the implementation of moral sanctions. These findings confirm that the salary and share deduction system is not only a loan security tool, but also a concrete manifestation of cooperative values: kinship, collective responsibility, and economic justice.

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.