Global economic instability and energy market volatility pose significant challenges to the accurate prediction of Indonesia's oil and gas export performance. This study develops a hybrid VAR–NN forecasting model that incorporates global oil prices and exchange rates as external variables, with the objective of improvi...
Mei Dina Putri Nadhifah, Aviolla Terza Damaliana, Shindi Shella May Wara· bit-Tech· 0 citations
Rainfall prediction plays an important role in supporting hydrometeorological disaster mitigation and weather-related decision-making. However, accurate rainfall prediction remains challenging because atmospheric processes are highly nonlinear and governed by complex interactions among multiple meteorological variables...
Preliminary evidence is provided that the predictive advantage of nonlinear STAR models depends on stock-specific statistical characteristics rather than model complexity alone, while highlighting the need for broader validation frameworks and exogenous predictors in future forecasting research.
It is demonstrated that integrating contextual language representations with sequential modeling, supported by an efficient LLM-assisted labeling strategy and class imbalance handling, provides an effective approach for Indonesian cyberbullying detection and offers a practical solution for large-scale social media cont...
F. Nafiah, Aviolla Terza Damaliana, K. M. Hindrayani· JOURNAL OF APPLIED INFORMATI...· 0 citations
The integration of Bagging, Stacked LSTM, and MBB improves model robustness and forecasting accuracy, and can support data-driven decision-making in economic policy, although further research is needed to incorporate additional variables and explore more advanced forecasting architectures.
