Capital markets play a strategic role in the global economy; however, high volatility often poses challenges for investors in making optimal investment decisions. Stock price prediction has become one of the key elements in effective portfolio management, but the complexity of market data demands more advanced analytical approaches. This study aims to explore the potential of Long Short-Term Memory (LSTM) models in predicting stock price movements and integrating these predictions into portfolio optimization strategies based on modern portfolio theory. The research methodology utilizes historical stock data from the S&P 500 and IDX Composite indices with daily frequency. The LSTM model is compared with Recurrent Neural Networks (RNN), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and accuracy. The LSTM model demonstrated superior performance with an MSE of 0.0018, RMSE of 0.042, and prediction accuracy of 91.5%, significantly outperforming RNN (87.3%), SVM (80.2%), and ANN (82.7%). The prediction results were then integrated into portfolio optimization using the Mean-Variance Optimization approach, resulting in an increase in expected returns from 8.5% to 12.3%, a reduction in risk from 6.2% to 5.8%, and an improvement in the Sharpe ratio from 1.37 to 2.12. This study demonstrates that the LSTM model not only excels in stock price prediction accuracy but also contributes significantly to enhancing portfolio management efficiency. This Deep Learning-based approach offers a more adaptive, data-driven investment strategy, supporting more informed decision-making in the dynamic capital market

Main Problem: There are differences in the influence of AI and Big Data on employee performance in previous research. Objective: Focus research by reviewing and analyzing whether Artificial Intelligence or AI has an influence on employee performance. Next, analyze whether Big Data affects employee performance. Originality: The Influence of AI and Big Data on Employee Performance. Method: To select the research sample, the proportional area random sampling method and regression equation were used to process the data with the help of the SPSS application. Results: In this research and discussion, it can be concluded that AI Big Data has an influence on the performance of employees at PT. Widya Robotics Yogyakarta, General Ahmad Yani International Airport Semarang, PT. Global Data Inspiration Yogyakarta.

The Research that entitled “The Influence of Interest Rate and Earnings Percapita To Saving In Banyumas Regency”. Data that used are secondary data : interest rate of deposit at public bank, GDRB according to Constant price in Banyumas Regency, sum up resident in Banyumas Regency, saving of Banyumas sociedy, period of year time are 2016-2021 aims to 1) partial analyzing the influence of interest rate an earning per capita to saving in Banyumas Regency (2) knowing the most factor effects to saving in Banyumas Regency.
The Result of analyzing during period 2016-2021 shows :

Saving mean in Banyumas Regency during the research period are Rp. 1.634,683 milliar, the mean of interest rate are 19,50%. The mean of Earnings percapita during the research period are Rp. 1.498.677,- its better than minimum regional wage, it’s mentioned indicate that the good enough society Banyumas earnings.
The correlation coefficient show that the variable of interest rate has a strong relation with saving, its mentioned of 0,596, The correlation coefficient of earnings percapita with saving are 0,943. It’s mean that retation of variable of earnings percapita has the strong relation with saving.
Partial effects from independent variable show that interest rate and earnings percapita have a significant effect. Earnings percapita is a most effect to saving its show by significance of alpha 0,000 and t value is 6,951 its above of t tables 2,18 interest rate has t value 3,238 with the significance of alpha 0,017.
Simultan effects show that independent variable (interest rate and earnings percapita) have an effect to saving with significance of alpha 5%, it’s mentioned proved with the F value 40,259 bigger than F tables 3,86 and with significances of alpha 0,000.
Based on elasticity of earnings percapita have a biggest effect to saving with the value 1,314.

Therefore, government of Banyumas Regency suggested to make-up of earnings percapita so that saving in Banyumas Regency can increase.