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M. Faisal

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Conference Jul 2026

Feature Selection and Performance Analysis for Heart Rate Estimation from Smartphone Photoplethysmography

Smartphone cameras enable continuous, equipment-free heart rate monitoring, yet the photoplethysmography (PPG) signals they capture are susceptible to movement, contact instability, and environmental variation that differ sharply from controlled validation settings. This study evaluated heart rate estimation from smart...

I. Azizah, Fatma Indriani, D. Nugrahadi et al. · 0 citations

TabKANet for Software Defect Prediction: An Oversampling and Feature-Selection Ablation Study

This study adapts TabKANet to the all-numerical, highly imbalanced SDP setting and empirically evaluates it against established baselines, using a structured ablation in order to isolate the contribution of oversampling and feature selection rather than to propose a new architecture.

Setyo Wahyu Saputro, M. Faza, Azhiman Saputra Setyo et al. · 0 citations
Review Open access Jul 2026

Improving Neutral Sentiment Classification in Indonesian E-Wallet Reviews Using Word2Vec and Easy Data Augmentation (EDA)

It is demonstrated that semantic representations and controlled lexical variation can jointly enhance minority-class recognition in short informal Indonesian text and highlight the importance of aligning embedding strategies with sequence architectures.

Muhammad Fattah Edric Camilo, Fatma Indriani, M. Faisal et al. · 0 citations
Open access Aug 2026

Comparative Evaluation of TabKANet with Oversampling and Feature Selection Ablation for Software Defect Prediction

TabKANet is a competitive architecture for all-numerical, highly imbalanced SDP, matching strong neural baselines and surpassing TabNet, where effective class weighting alone suffices and SMOTE is counter-productive.

Muhammad Faza Azhiman Saputra, Setyo Wahyu Saputro, M. Faisal et al. · 0 citations

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