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About

Ikhsan Purnama Santika is an Indonesian researcher whose work sits at the intersection of speech recognition, robotic control, and intelligent systems. His research focuses on developing practical, accessible automation solutions using machine learning and signal processing techniques applied to robotic platforms — particularly 5 Degrees of Freedom (DoF) arm robots built on Arduino microcontrollers. Santika's most influential contribution, cited 36 times, demonstrates the integration of Linear Predictive Coding (LPC) for speech feature extraction combined with Adaptive Neuro-Fuzzy Inference System (ANFIS) to enable voice-controlled robotic manipulation — a notable achievement in bridging human-computer interaction with physical automation. His complementary 2017 study (12 citations) explored an alternative approach using Mel-Frequency Cepstrum Coefficients (MFCC) paired with K-Nearest Neighbors (KNN), offering researchers a comparative perspective on speech-driven robotic control methodologies. Beyond voice interfaces, his work on colored object sorting using Artificial Neural Networks (11 citations) highlights his broader commitment to intelligent industrial automation. Collectively, Santika's research offers practically implementable frameworks that make advanced robotics more approachable, making his publications particularly valuable for students and engineers working at the frontier of embedded systems, machine learning, and human-robot interaction.