Author

Eko Sediyono

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Open access Sep 2026

Comparative Evaluation of LSTM-Based Deep Learning Models for Software Effort Estimation

Software development effort estimation is a critical aspect of effective project planning, as inaccurate predictions can lead to cost overruns, schedule delays, and incomplete system implementation. This study evaluates five LSTM-based deep learning architectures—Standard LSTM, CNN-BiLSTM, Residual LSTM, LSTM-GRU, and...

Santa Margita, Eko Sediyono, S. Y. J. Prasetyo et al. · HighTech and Innovation Jour... · 0 citations

Open access 2026

Earthquake Damage Risk Classification Using Machine Learning Models Based on Built-Up Area Indices from Satellite Imagery

One of the challenges in assessing earthquake damage risk in areas with high seismic activity and limited data is the lack of a detailed building inventory and the absence of available data. Therefore, a remote sensing and machine learning framework is needed that can utilize the built-up area index with NDBI from mult...

Gunawan Prayitno, Eko Sediyono, Irwan Sembiring et al. · International Journal of Adv... · 0 citations