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Menampilkan 1–2 dari 2 artikel
Evaluating Explainable Artificial Intelligence Methods for Interpretable Machine Learning Models in Large Scale Enterprise Data Analytics Systems
Indra Ava Dianta
; Greget Widhiati
; Andreas Tigor Oktaga
Big Data Analytics and Data Science
Vol 1
, No 1
(2026)
Explainable Artificial Intelligence (XAI) has become a critical area of research within artificial intelligence, focusing on improving the transparency and interpretability of machine learning (ML) models, often referred to as "black-box" models. The need for XAI techniques arises from the inherent complexity of ML models, which can make their decision-making processes difficult for users to understand. This study investigates various XAI techniques, including LIME (Local Interpretable Model-agn...
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Federated Hybrid CNN GRU and COBCO Optimized Elman Neural Network for Real Time DDoS Detection in Cloud Edge Environments
Danang Danang
; Maya Utami Dewi
; Greget Widhiati
International Journal of Electrical Engineering, Mathematics and Computer Science
Vol 2
, No 2
(2025)
Improvement amount Distributed Denial of Service (DDoS) attacks in cloud infrastructure and edge computing demands solution adaptive, distributed, and efficient detection in a way computing. Research This propose an optimized Federated Learning (FL) based DDoS detection model using Centroid Opposition-Based Bacterial Colony Optimization (COBCO) to training the Elman Neural Network (ENN). The proposed architecture consists of of two components Main: on the edge node side, a hybrid Convolutional N...
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