Machine Learning and Quantum Machine Learning for Indonesian Weather Forecasting

Overview

Weather prediction using local Indonesian data rather than generic benchmarks, so the model has to deal with the actual seasonal and regional patterns that matter for the region.

Approach

• Preprocessing and feature engineering for local climate time series
• Classical ML baselines to establish a fair comparison point
• Hybrid ML-QML models evaluated on the same splits and metrics

Outcome

This became my undergraduate thesis at Universitas Negeri Malang (2026), titled “Optimization of Classical and Quantum Machine Learning Models for Weather Forecasting in Indonesia”. Training and validation metric plots are included in the repository, together with the code path for the QML experiments.