Gold, as a valuable commodity, has been a primary focus in the global financial market. It is often utilized as an investment instrument due to the belief in its potential price appreciation. However, the unpredictable and complex movement of gold prices poses a significant challenge in investment decision-making. Therefore, this research aims to address this issue by proposing the use of the Long Short-Term Memory (LSTM) model in time series analysis. LSTM is a robust approach to understanding patterns and trends in gold price data over time. In the context of time series analysis, historical gold price data includes daily, weekly, and monthly datasets. Each model with its respective dataset is useful for identifying patterns in gold prices. The daily model achieves an MSE of 452.2284140627481 and an RMSE of 21.26566279387379. The weekly model achieves an MSE of 1346.1816584357384 and an RMSE of 36.69034830082345. The monthly model achieves an MSE of 11649.597907584808 and an RMSE of 107.93330305139747. With these RMSE results, the LSTM model can predict gold prices effectively. Based on the trained models, it can also be concluded that gold prices exhibit long-term temporal dependence.

Poverty is a complex problem because it relates to various aspects of human life. In Indonesia, there is one province that has a very high percentage of poverty, namely East Java Province. Although from year to year the poverty rate has decreased, when viewed from the national level it is still very far from the government's expectations of reducing the poverty rate. Cases of poverty can be modeled by Econometrics. Econometric models are often applied to problems involving one or more related equations. One method that can be used to solve several interrelated equations because there is a correlation error regression between one another, namely Seemingly Unrelated Regression which is usually abbreviated as SUR, in this case Spatial Seemingly Unrelated Regression (SUR-Spatial) is development that takes into account the spatial influence between locations. From the results of tests conducted in the SUR-Spatial Lagrange Multiplier model, the poverty data generated by the East Java Province is the SUR-Spatial Autoregressive Model (SUR-SAR). So with the SUR-SAR model it can be seen that the variable that has a significant effect on the percentage of poor people is the growth rate of Gross Regional Domestic Product based on the constant price of the minimum wage for each district, as well as the average length of school years. Meanwhile, the Poverty Depth Index has an effect because of the growth rate of Gross Regional Domestic Product on the basis of constant prices and the average length of schooling. The Poverty Severity Index is influenced by the growth rate of Gross Regional Domestic Product at constant prices and average years of schooling.

Industri sektor perbankan di Indonesia telah banyak mengalami perkembangan dengan signifikan dalam peran serta memepengaruhi perkembangan ekonomi Indonesia di era digital. Perlindungan konsumen merupakan pokok utama yang dibahas dalam regulasi dan ketentuan perlindungan konsumen untuk mengoptimalisasikan kebijakan dalam penggunaan produk perbankan pada era digital saat ini. Penelitian ini bertujuan untuk menganalisis ketentuan dan hukum perlindungan konsumen bagi konsumen lembaga jasa keuangan dalam mengoptimalisasikan kebijakan dalam penggunaan produk perbankan  pada era digital. Metode yang digunakan adalah  penelitian  menggunakan pendekatan normatif dengan paradigma post-positivisme, bahwa guna terciptanya perlindungan hukum terhadap konsumen. Perlindungan konsumen merupakan upaya untuk memberi penjelasaan tentang  pengetahuan dan pemahaman atas produk dan/atau layanan yang akan digunakan atau dimanfaatkan oleh konsumen. Perbankan yang mempunyai produk berusaha memberikan kepastian hukum dan ketentuan lainnya untuk melindungi konsumen dalam pemenuhan hak dan kewajiban konsumen di sektor jasa keuangan dengan memperhatikan cara agar terhindar dari dampak  negatif di era digital.