The objective of this study is to predict unemployment in Indonesia in the wake of the demographic dividend. The sample used in this study is the unemployment data from 1990 to 2022 from the Indonesian Central Bureau of Statistics database. Using non-seasonal ARIMA (Autoregressive Integrated...

The structural modeling of open-high-low-close (OHLC) data contained within the candlestick chart is crucial to fnancial practice. However, the inherent constraints in OHLC data pose immense challenges to its structural modeling. Models that fail to process these constraints may yield results...

Over the past five years, emerging economies have consistently progressed toward achieving greater economic independence. The aviation industry has played a significant role in driving this progress. Accurately forecasting the future demand for air travel is crucial for making long-term...

There has been significant interest in integrating sentiment analysis with graph neural networks (GNNs) for stock prediction tasks. This article thoroughly reviews the application of GNNs in conjunction with sentiment analysis for stock prediction. This study introduces the fundamental concepts...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies’ expenditures, so even small improvement in new approaches can considerably reduce these items’ total inventory. This paper aims to present a new hybrid forecasting...