Abstract:This study aims to empirically analyze the effect of exchange rates and interest rates on the stock prices of banking companies listed on the Indonesia Stock Exchange during the 2020-2024 period. The research employs a quantitative…
uantitative approach with a causal-associative design and utilizes secondary data obtained from official publications of Bank Indonesia (BI) and the Indonesia Stock Exchange (IDX). The research population consists of 45 banking companies, from which 20 companies meeting the sampling criteria were selected using purposive sampling. Data analysis was conducted comprehensively through descriptive analysis, classical assumption tests, multiple linear regression, and hypothesis testing with the assistance of SPSS software. The findings reveal that, partially, exchange rates have a significant negative effect on stock prices, and interest rates also exert a significant negative effect. Furthermore, simultaneous testing confirms that both independent variables significantly and negatively influence banking stock prices. These results highlight that macroeconomic volatility, particularly exchange rate fluctuations and interest rate movements, are crucial determinants to be considered in capital market analysis. Academically, this study contributes to the literature on the relationship between macroeconomic indicators and stock price dynamics, while practically, the results may serve as a reference for investors in making investment decisions, for policymakers in formulating economic stabilization strategies, and for banking institutions in anticipating market risks arising from both global and domestic economic uncertainty.
Abstract:The capital market has become a cornerstone of modern economies, facilitating the flow of funds between investors and business entities to support growth and innovation. However, interest in investing in the Indonesian capital…
apital market still faces significant challenges, particularly in terms of risk understanding, perception, and individual motivation for investment. This research aims to explore the factors influencing individual investment interest in PT. Indonex Bangun Investama, a key player in the Indonesian capital market. The research adopts a quantitative approach involving 82 active investors of PT. Indonex Bangun Investama. Data analysis utilizes various statistical techniques such as normality tests, multicollinearity tests, and multiple linear regression analysis to examine the impact of risk, motivation, and investment knowledge variables on investment interest. The analysis results indicate that risk and motivation significantly affect investment interest, while investment knowledge, although important, does not significantly influence investment interest individually. These findings provide deeper insights into the psychological and economic factors underlying individual investment decisions in the Indonesian capital market. The implications of this research suggest the need for a more holistic and strategic educational approach to enhance financial literacy and effective risk mitigation in individual investment strategies. Thus, this research makes a significant contribution to the development of education strategies and risk management in the Indonesian capital market context, laying a foundation for further discussions on expanding accessibility and participation in investment among the public.
Abstract:The rapid development of globalization compels companies to enhance the quality of their products and services to compete in the market. The primary goal of companies is to maximize corporate value, which reflects the well-being…
ll-being of shareholders and attracts investors’ interest. Corporate value is often gauged by the stock price in the capital market, making it crucial for companies to plan sound financial strategies. This research focuses on the banking sector listed on the Indonesia Stock Exchange (IDX) from 2021 to 2023, evaluating the influence of investment policy, dividend policy, and profitability on corporate value. The study employs a descriptive quantitative method using secondary data from the companies’ financial reports. Multiple linear regression analysis is used to assess the relationships between these variables. The results indicate that investment policy and profitability have a positive but not significant effect on corporate value, while dividend policy has a significant positive impact. Corporate value is also affected by stock price fluctuations, which are often inconsistent. These findings affirm that dividend policy is a crucial factor in enhancing corporate value, while investment policy and profitability, although important, do not have a significant impact within the study period. Overall, these independent variables collectively have a significant influence on corporate value in the banking sector on the IDX. This research provides insights for company management in formulating effective strategies to increase corporate value.
Abstract:Abstract: The materials sector is one of the stock markets sectors that attracts investors due to the high level of construction activity in Indonesia, which supports long-term growth. Stock price movements are influenced…
d by various factors, requiring investors to determine the appropriate timing for buying, selling, or holding stocks. Therefore, this study aims to predict stock prices in the materials sector using a combination of CNN–BiLSTM algorithms. The research data were obtained from Yahoo Finance and processed through min–max normalization, data splitting, sliding window, model implementation, and evaluation stages. Testing was conducted on INTP and SMGR stocks with data split scenarios ranging from 60:40 to 90:10. The results show that CNN–BiLSTM performs best with a 90:10 data split, with minimum MSE and MAPE values of 0.000153 and 2.471% for INTP, and 0.000199 and 2.208% for SMGR, respectively. These findings indicate that increasing the proportion of training data improves the model's ability to learn historical patterns and produce more stable predictions.
Keywords: CNN-BILSTM; materials sector; stock
Abstrak: Sektor materials merupakan salah satu sektor saham yang diminati investor karena tingginya aktivitas pembangunan di Indonesia yang mendorong pertumbuhan jangka panjang. Pergerakan harga saham dipengaruhi oleh berbagai faktor sehingga investor perlu menentukan waktu transaksi yang tepat. Oleh karena itu, penelitian ini bertujuan memprediksi harga saham sektor materials menggunakan kombinasi algoritma CNN–BiLSTM. Data penelitian diperoleh dari Yahoo Finance dan diproses melalui tahapan normalisasi min–max, pembagian data, sliding window, implementasi model, serta evaluasi. Pengujian dilakukan pada saham INTP dan SMGR dengan skenario pembagian data 60:40 hingga 90:10. Hasil menunjukkan bahwa CNN–BiLSTM menghasilkan performa terbaik pada pembagian data 90:10, dengan nilai MSE dan MAPE minimum masing-masing sebesar 0.000153 dan 2.471% untuk INTP, serta 0.000199 dan 2.208% untuk SMGR. Temuan ini mengindikasikan bahwa peningkatan porsi data latih meningkatkan kemampuan model dalam mempelajari pola historis dan menghasilkan prediksi yang lebih stabil.
Kata kunci: CNN-BILSTM; saham; sektor materials
Abstract:Abstract: The capital market plays an important role in describing the economic conditions of a country, and the IHSG is used as the main indicator to observe the movement of all stocks on the Indonesia Stock Exchange. Because…
ecause stock data is volatile and non-linear, the forecasting process becomes challenging, requiring methods that can capture historical patterns more accurately. This study aims to predict IHSG movements using the Long Short-Term Memory (LSTM) model to generate stable short-term predictions. Historical IHSG data was used to train the model, and accuracy was evaluated using Mean Squared Error (MSE). The results show that the model obtained an MSE 6784.0207, RMSE 82.3652 and MAPE 0.88%, indicating a relatively low prediction error rate. The visualization shows that the model's predictions are very close to the actual data, and the 60-day forecasting results show a potential increase in the IHSG of 1.05%. Thus, the LSTM model is capable of providing fairly accurate IHSG predictions and can be a useful tool for investors in analyzing short-term market movements.
Keywords: forecasting; JCI; long short term memory
Abstrak: Pasar modal memiliki peran penting dalam menggambarkan kondisi ekonomi suatu negara, dan IHSG digunakan sebagai indikator utama untuk melihat pergerakan seluruh saham di Bursa Efek Indonesia. Karena data saham bersifat fluktuatif dan tidak linear, proses peramalan menjadi tantangan, sehingga dibutuhkan metode yang mampu menangkap pola historis secara lebih akurat. Penelitian ini bertujuan memprediksi pergerakan IHSG menggunakan model Long Short-Term Memory (LSTM) untuk menghasilkan prediksi jangka pendek yang stabil. Data historis IHSG digunakan untuk melatih model, kemudian akurasi dievaluasi menggunakan Mean Squared Error (MSE). Hasil penelitian menunjukkan bahwa model memperoleh nilai MSE 6784.0207, RMSE 82.3652 dan MAPE 0.88% yang menandakan tingkat kesalahan prediksi relatif rendah. Visualisasi menunjukkan bahwa prediksi model sangat mendekati data aktual, dan hasil forecasting 60 hari ke depan memperlihatkan potensi kenaikan IHSG sebesar 1,05%. Dengan demikian, model LSTM mampu memberikan prediksi IHSG yang cukup akurat dan dapat menjadi alat bantu bagi investor dalam menganalisis pergerakan pasar jangka pendek.
Kata kunci: peramalan; JCI; memori jangka pendek
Abstract: Abstract – Price forecasting is a part of economic decision making. Forecasting the daily rise and fall of gold prices can help investors decide when to buy or sell the commodity. The price of gold depends on many factors…
many factors such as the price of other precious metals, the price of crude oil, the performance of the stock exchange, and the exchange rate of currencies. This study discusses gold price forecasting using the multiple linear regression method. The results of this study indicate that the best model is in the data distribution of 70%: 30% for training and testing, with a MAPE of 4.7% Based on these results, it can be concluded that the use of multiple linear regression method produces a fairly good model for gold prices forecasting. Besides, the correlation analysis show that the price of other precious metals greatly influences the price of gold where in this case the silver price whose correlation value is 0.87.
Keywords: forecasting, gold investment, multiple linear regression
Abstrak: Peramalan harga merupakan bagian dari pengambilan keputusan ekonomi. Melakukan peramalan terhadap kenaikan dan penurunan harga emas harian dapat membantu investor memutuskan kapan harus membeli atau menjual komoditas. Harga Emas bergantung pada banyak faktor seperti harga logam mulia lainnya, harga minyak mentah, kinerja bursa saham, dan nilai tukar mata uang. Penelitian ini membahas peramalan harga emas dengan menggunakan metode regresi linear ganda. Hasil dari penelitian ini menunjukkan bahwa model terbaik terdapat pada pembagian data pelatihan 70% dan pengujian 30%, dengan MAPE sebesar 4.7%. Berdasarkan hasil tersebut dapat diambil kesimpulan bahwa penggunaan metode regresi linear ganda menghasilkan model yang cukup baik untuk peramalan harga emas. Selain itu, analisis korelasi menunjukkan bahwa harga logam mulia lainnya sangat mempengaruhi harga emas dimana dalam hal ini variabel harga perak yang nilai korelasinya 0.87.
Kata kunci: peramalan; investasi emas, regresi linear ganda
Abstract:Abstract: Money Market Mutual Funds are a short-term and low-risk investment vehicle suitable for novice investors. The large list of Money Market Mutual Funds for sale makes it difficult for novice investors to choose the…
he best one. Therefore, in selecting Money Market Mutual Funds, a decision support system is needed by using the AHP (Analytical Hierarchical Process) method. Calculations using the AHP method can produce ratings that can be used as a reference in selecting Money Market Mutual Funds. The highest-ranking result in this study is Batavia Dana Kas Maxima.
Keywords: AHP; Decision Support System; Money Market Mutual Funds
Abstrak: Reksa Dana Pasar Uang adalah sarana investasi jangka pendek dan berisiko rendah yang cocok bagi investor pemula. Banyaknya daftar Reksa Dana Pasar Uang yang dijual membuat investor pemula kesulitan dalam memilih yang terbaik. Oleh sebab itu, diperlukan sistem pendukung keputusan dalam memilih Reksa Dana Pasar Uang dengan menggunakan metode AHP (Analytical Hirearchy Process). Perhitungan metode AHP dapat menghasilkan peringkat yang dapat dijadikan acuan dalam memilih Reksa Dana Pasar Uang. Hasil peringkat tertinggi pada penelitian ini adalah Reksa Dana Pasar Uang (RDPU) Batavia Dana Kas Maxima.
Kata kunci: AHP; Reksa Dana Pasar Uang; Sistem Pendukung Keputusan
Abstract:The Indonesian capital market plays a pivotal role in mobilising long-term financing for corporations and providing investment opportunities to the public. However, persistent stock fraud cases undermine market integrity…
and investor confidence. This study aims to evaluate the effectiveness of the existing legal framework for investor protection against stock fraud, analyse its practical implementation, and recommend measures to strengthen both preventive and repressive mechanisms. Employing a normative legal research design with a qualitative approach, the study integrates statute, conceptual, and case approaches, focusing on Law No. 8 of 1995 on Capital Markets, OJK regulations, the Criminal Code, and notable cases such as PT Hanson International Tbk. The findings reveal that while the legal framework normatively aligns with the Legal Protection Theory, Justice Theory, and Legal Effectiveness Theory, substantial gaps remain between regulation and enforcement. Weak supervisory coordination, delayed intervention, lengthy judicial processes, and low investor legal literacy reduce effectiveness. Recommended reforms include adopting regtech and suptech, enhancing cross-agency data integration, implementing AI-based surveillance, establishing a specialised capital market court, and strengthening investor education. The study concludes that combining regulatory improvements, adaptive enforcement, and public legal empowerment is essential to safeguard investors, maintain market integrity, and promote sustainable economic growth.
Abstract:This study explores the impact of asset structure and sales growth on capital structure, emphasizing the moderating influence of profitability. As firms navigate the complexities of financing decisions, understanding how…
these variables interact is crucial for optimizing capital structure. The findings reveal that asset structure and sales growth significantly affect capital structure, with profitability playing a critical role in moderating these relationships. Firms with substantial tangible assets are better positioned to leverage debt financing, while those demonstrating strong sales growth are viewed favorably by investors and creditors. However, the extent to which sales growth influences capital structure is contingent upon profitability; high profitability enables firms to capitalize on growth opportunities, whereas low profitability may inhibit their capacity to leverage growth potential. Empirical research supports these conclusions, indicating that asset structure, sales growth, and profitability significantly shape capital structure decisions across various industries. Ultimately, this study provides valuable insights for financial managers, highlighting the importance of balancing growth aspirations with profitability to achieve effective capital structure management. This, in turn, can lead to sustained competitive advantage, a state where a firm outperforms its competitors over a prolonged period in a dynamic economic environment.
Abstract:This research examines the intricate relationships between company size, growth in cash flow, and stock performance, revealing complexities that challenge traditional financial analysis. While company size is often associated…
iated with stable stock performance due to advantages such as economies of scale and market power, the findings indicate that size alone does not positively impact stock performance. Furthermore, the study demonstrates that growth in cash flow does not significantly moderate the relationship between company size and stock performance. This suggests that external factors, such as regulatory changes or market sentiment, may play a more decisive role. The results underscore that cash flow, while an important indicator of financial health, does not enhance the influence of company size on stock performance, particularly in certain industries where external conditions prevail. This underscores the need for a more comprehensive evaluation approach that considers a broader range of factors when assessing stock performance. It's time to move beyond traditional metrics like profitability and cash flow growth and equip ourselves with a more robust set of tools for analysis. Ultimately, this research advocates for a multifactorial approach to stock performance evaluation, emphasizing the importance of understanding the interplay between various variables, including industry trends and macroeconomic conditions. By adopting this comprehensive perspective, investors and analysts can make more informed decisions and strategies, enhancing their ability to navigate the complexities of the financial markets.