Author

D. Thifal

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Open access Jul 2026

A Comparative Evaluation of Various Imputation Methods for LSTM-Based Climatological Time Series Forecasting

Missing values substantially degrade the reliability of environmental time-series forecasting; however, prior studies largely evaluate imputation methods in isolation without systematically linking missingness mechanisms to deep learning forecasting performance. To address this gap, this study proposes a mechanism-awar...

D. Thifal, Aji Prasetya Wibawa, Adelia Desyana Eka Putri et al. · Jurnal Informatika · 0 citations

Open access Jul 2026

Assessing the Effectiveness of Statistical and Temporal Imputation Methods for Bi-LSTM-Based Forecasting on Environmental and Climate Time Series Data

Time series data in climatology and environmental research are highly susceptible to missing values that can disrupt temporal structures and degrade forecasting performance. This study evaluates the effectiveness of several imputation methods in improving the predictive performance of a Bidirectional Long Short-Term Me...

Adelia Desyana Eka Putri, Aji Prasetya Wibawa, Adelia Khansa Ristiaputri et al. · Matrik · 0 citations